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All local districts in New York State are required to accept the revised DOH-4220 for non-MAGI Medicaid applicants (Aged 65+, Blind, Disabled) (including for coverage of long-term care services), Medicare Savings Program, the Medicaid Buy-In Program fr Working People with Disabilities. Districts must also continue to accept the LDSS-2921, although it only makes sense to use this when someone is applying for both Medicaid and some other public benefit covered by the Common Application, such as the income benefits such as Safety Net Assistance. The DOH-4220 - Access NY Health Care application can be used for all Medicaid benefits -- including for those who want to apply for coverage of Medicaid long-term care -- whether through home care online viagra cost or for those in a nursing home.j (with the addition of the Supplement Aform, described below). DO NOT USE THE DOH-4220 FOR.

WHAT IF THE APPLICANT CANNOT SIGN THE APPLICATION?. DOH APPLICATION - WHERE TO FIND ONLINE Check here for updates and changes English Spanish This article was authored by the Evelyn Frank Legal Resources Program of New York Legal Assistance Group..

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Markets from 2016 to 2018, using data from the Agency for Healthcare Research and Quality (AHRQ) Compendium of U.S. Health Systems and commercial data on online viagra cost physician-system affiliation. The research team from Mathematica and AHRQ found that physician consolidation into health systems increased in nearly all (92 percent) metropolitan statistical areas from 2016 to 2018. Of the 382 metropolitan statistical areas, 113 had more online viagra cost than half of their physicians in health systems in 2018.

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To the does viagra make your dick bigger Can you buy ventolin over the counter in usa Editor. Qatar had a first wave of s with severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) from March through June 2020, after which approximately 40% of the population had detectable does viagra make your dick bigger antibodies against erectile dysfunction. The country subsequently had two back-to-back waves from January through May 2021, triggered by the introduction of the B.1.1.7 (or alpha) and B.1.351 (or beta) variants.1 This created an epidemiologic opportunity to assess res. Using national, federated databases that have captured all erectile dysfunction–related data since the onset does viagra make your dick bigger of the viagra (Section S1 in the Supplementary Appendix, available with the full text of this letter at NEJM.org), we investigated the risk of severe disease (leading to acute care hospitalization), critical disease (leading to hospitalization in an intensive care unit [ICU]), and fatal disease caused by res as compared with primary s in the national cohort of 353,326 persons with polymerase-chain-reaction (PCR)–confirmed between February 28, 2020, and April 28, 2021, after exclusion of 87,547 persons with a vaccination record.

Primary was defined as the first PCR-positive swab. Re was defined as the first PCR-positive swab obtained at least 90 days after does viagra make your dick bigger the primary . Persons with re were matched to those with primary in a 1:5 ratio according to sex, 5-year age group, nationality, and calendar week of the PCR test date (Fig. S1 and Table S1 in the Supplementary Appendix) does viagra make your dick bigger.

Classification of severe, critical, and fatal erectile dysfunction treatment followed World Health Organization guidelines, and assessments does viagra make your dick bigger were made by trained medical personnel through individual chart reviews. Table 1. Table 1 does viagra make your dick bigger. Severity of erectile dysfunction Res as Compared with Primary s in the Population of Qatar.

Of 1304 identified res, 413 (31.7%) does viagra make your dick bigger were caused by the B.1.351 variant, 57 (4.4%) by the B.1.1.7 variant, 213 (16.3%) by “wild-type” viagra, and 621 (47.6%) were of unknown status (Section S1 in the Supplementary Appendix). For reinfected persons, the median time between first and re was 277 days (interquartile range, 179 to 315). The odds of severe disease at re were 0.12 times (95% confidence interval does viagra make your dick bigger [CI], 0.03 to 0.31) that at primary (Table 1). There were no does viagra make your dick bigger cases of critical disease at re and 28 cases at primary (Table S3), for an odds ratio of 0.00 (95% CI, 0.00 to 0.64).

There were no cases of death from erectile dysfunction treatment at re and 7 cases at primary , resulting in an odds ratio of 0.00 (95% CI, 0.00 to 2.57). The odds of the does viagra make your dick bigger composite outcome of severe, critical, or fatal disease at re were 0.10 times (95% CI, 0.03 to 0.25) that at primary . Sensitivity analyses were consistent with these results (Table S2). Res had 90% lower odds of resulting in hospitalization does viagra make your dick bigger or death than primary s.

Four res were severe enough to lead to acute care hospitalization. None led to hospitalization in an ICU, and none ended does viagra make your dick bigger in death. Res were rare and were generally mild, perhaps because of the primed immune system after does viagra make your dick bigger primary . In earlier studies, we assessed the efficacy of previous natural as protection against re with erectile dysfunction2,3 as being 85% or greater.

Accordingly, for a person who has already had a primary , the risk of having a severe re is only approximately 1% of the risk of does viagra make your dick bigger a previously uninfected person having a severe primary . It needs to be determined whether such protection against severe disease at re lasts for a longer period, analogous to the immunity that develops against other seasonal “common-cold” erectile dysfunctiones,4 which elicit short-term immunity against mild re but longer-term immunity against more severe illness with re. If this were the case with erectile dysfunction, the viagra (or at least the variants studied to date) could adopt a more benign pattern of when it becomes does viagra make your dick bigger endemic.4 Laith J. Abu-Raddad, Ph.D.Hiam Chemaitelly, M.Sc.Weill Cornell Medicine–Qatar, Doha, Qatar [email protected]Roberto Bertollini, M.D., M.P.H.Ministry of Public Health, Doha, Qatarfor the National Study Group for erectile dysfunction treatment Epidemiology Supported by the Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core at Weill Cornell Medicine–Qatar.

The Ministry does viagra make your dick bigger of Public Health. Hamad Medical Corporation does viagra make your dick bigger. And Sidra Medicine. The Qatar Genome Program supported the does viagra make your dick bigger viral genome sequencing.

Disclosure forms provided by the authors are available with the full text of this letter at NEJM.org. This letter was does viagra make your dick bigger published on November 24, 2021, at NEJM.org. Members of the National Study Group for erectile dysfunction treatment Epidemiology are listed in the Supplementary Appendix, available with the full text of this letter at NEJM.org. 4 References1 does viagra make your dick bigger.

Abu-Raddad LJ, Chemaitelly H, does viagra make your dick bigger Butt AA. Effectiveness of the BNT162b2 erectile dysfunction treatment against the B.1.1.7 and B.1.351 variants. N Engl J Med 2021;385:187-189.2 does viagra make your dick bigger. Abu-Raddad LJ, Chemaitelly H, Coyle P, et al.

erectile dysfunction antibody-positivity protects against re for does viagra make your dick bigger at least seven months with 95% efficacy. EClinicalMedicine 2021;35:100861-100861.3. Abu-Raddad LJ, does viagra make your dick bigger Chemaitelly H, Malek JA, et al. Assessment of does viagra make your dick bigger the risk of severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) re in an intense reexposure setting.

Clin Infect Dis 2021;73(7):e1830-e1840.4. Lavine JS, Bjornstad ON, Antia R does viagra make your dick bigger. Immunological characteristics govern the transition of erectile dysfunction treatment to endemicity. Science 2021;371:741-745.10.1056/NEJMc2108120-t1Table does viagra make your dick bigger 1.

Severity of erectile dysfunction Res as Compared with Primary s in the Population of Qatar. Disease Outcome*Re†Primary †Odds Ratio (95% CI)no does viagra make your dick bigger. Of persons with outcome/no does viagra make your dick bigger. Of persons with that was not severe, critical, or fatalSevere disease4/1300158/60950.12 (0.03–0.31)Critical disease0/130028/60950.00 (0.00–0.64)Fatal disease0/13007/60950.00 (0.00–2.57)Severe, critical, or fatal disease4/1300193/60950.10 (0.03–0.25)The Clinical Implications of Basic Research series has focused on highlighting laboratory research that could lead to advances in clinical therapeutics.

However, the path between the laboratory and the bedside does viagra make your dick bigger runs both ways. Clinical observations often pose new questions for laboratory investigations that then lead back to the clinic. One of does viagra make your dick bigger a series of occasional articles drawing attention to the bedside-to-bench flow of information is presented here, under the Basic Implications of Clinical Observations rubric. We hope our readers will enjoy these stories of discovery, and we invite them to submit their own examples of clinical findings that have led to insights in basic science.

The pathogenesis of severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) is incompletely understood, with its effects on multiple organ systems1 and the syndrome of “long erectile dysfunction treatment” occurring long after the resolution of .2 The development of multiple efficacious treatments has been critical in the control of the viagra, but their efficacy has been limited by the appearance of viral does viagra make your dick bigger variants, and the treatments can be associated with rare off-target or toxic effects, including allergic reactions, myocarditis, and immune-mediated thrombosis and thrombocytopenia in some healthy adults. Many of these phenomena are likely to be immune-mediated.3 How can we understand this does viagra make your dick bigger diversity in immune responses in different persons?. Figure 1. Figure 1 does viagra make your dick bigger.

Anti-idiotype Antibodies and erectile dysfunction. Both severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) and the treatments against it elicit antibodies to the spike protein that the viagra uses to bind does viagra make your dick bigger to the angiotensin-converting–enzyme 2 (ACE2) receptor on target cells. The receptor is widely expressed. These antibodies does viagra make your dick bigger are called Ab1.

The idiotype portions of Ab1 that bind and neutralize the spike protein have distinctive sequences in complementarity-determining region 3 (CDR3), and those antibody-binding regions can themselves elicit antibody responses called anti-idiotype does viagra make your dick bigger (Ab2) antibodies as a means of down-regulation. Ab2 antibodies can act in several ways. They can bind to the protective neutralizing Ab1 antibody, resulting does viagra make your dick bigger in immune-complex formation and clearance, thus impairing Ab1 efficacy. Some of the Ab2 binding regions, or paratopes, can also mirror the spike protein itself and bind to the same target as the spike protein, the ACE2 receptor.

That binding could, in theory, exert several different — but not necessarily mutually exclusive — effects on the cell, depending on the nature of the Ab2 antibodies does viagra make your dick bigger and the role of the receptors in the cell. For example, it could potentially block ACE2 function by competitively inhibiting normal ligand interactions. Alternatively, it could stimulate ACE2 function by triggering the receptor, affect expression of ACE2 after binding by down-regulating or internalizing ACE2, or, after binding the cells, induce a complement-mediated or immune-cell does viagra make your dick bigger attack on ACE2-expressing cells.One way of thinking about the complexity of the immune response is through the lens of anti-idiotype immune responses. The Network Hypothesis, formulated in 1974 by Niels Jerne, described a mechanism by which the antibody responses to an antigen themselves induced downstream antibody does viagra make your dick bigger responses against the antigen-specific antibody.4 Every antibody that is induced and specific for an antigen (termed “Ab1” antibody) has immunogenic regions, particularly in their variable-region antigen-binding domains, that are unique as a result of genetic recombination of immunoglobulin variable, diversity, and joining (VDJ) genes.

VDJ recombination results in new and therefore immunogenic amino acid sequences called idiotopes, which are then capable of inducing specific antibodies against Ab1 antibodies as a form of down-regulation. A similar paradigm does viagra make your dick bigger has been proposed for T cells. However, these regulatory immune responses are also capable of doing much more. The paratopes, or antigen-binding domains, of some of the resulting anti-idiotype (or “Ab2”) antibodies that are specific for Ab1 can does viagra make your dick bigger structurally resemble that of the original antigens themselves.

Thus, the Ab2 antigen-binding region can potentially represent an exact mirror image of the initial targeted antigen in the Ab1 response, and Ab2 antibodies have even been examined for potential use as a surrogate for the antigen in treatment studies. However, as a does viagra make your dick bigger result of this mimicry, Ab2 antibodies also have the potential to bind the same receptor that the original antigen was targeting (Figure 1). Ab2 antibodies binding to the original receptor on normal cells therefore have the potential to does viagra make your dick bigger mediate profound effects on the cell that could result in pathologic changes, particularly in the long term — long after the original antigen itself has disappeared.This aspect of regulation of immune-cell responses was postulated by Plotz in 1983 as a possible cause of autoimmunity arising after viral 5 and has since been supported experimentally by direct transfer of anti-idiotype antibodies. Ab2 antibodies generated against the enteroviagra coxsackieviagra B3 in mice can bind myocyte antigens, resulting in autoimmune myocarditis,6 and anti-idiotype responses can act as acetylcholine receptor agonists, leading to myasthenia gravis symptoms in rabbits.7 In addition, by displaying the mirror image of the viral antigen, Ab2 alone can even mimic the deleterious effects of the viagra particle itself, as has been shown with bovine viral diarrhea viagra antigen.8For erectile dysfunction , attention centers on the spike (S) protein and its critical use of the angiotensin-converting–enzyme 2 (ACE2) receptor to gain entry into the cell.

Given its does viagra make your dick bigger critical role in regulating angiotensin responses, many physiological effects can be influenced by ACE2 engagement.9 The S protein itself has a direct effect on suppressing ACE2 signaling by a variety of mechanisms and can also directly trigger toll-like receptors and induce inflammatory cytokines.10 Anti-idiotype responses may affect ACE2 function, resulting in similar effects. However, preclinical and clinical assessments of antibody responses to erectile dysfunction treatments have focused solely on Ab1 responses and viagra-neutralizing efficacy. The delineation of potential anti-idiotype responses has inherent difficulties because of the polyclonal nature of responses, dynamic kinetics, and the concurrent presence of both Ab1 and Ab2 does viagra make your dick bigger antibodies. Furthermore, ACE2 expression within cells and tissues can be variable.

The different treatment constructs (RNA, DNA, adenoviral, and protein) are also likely to have differential effects on Ab2 induction or in the mediation of treatment effects that differ does viagra make your dick bigger from responses to . Some off-target effects may does viagra make your dick bigger not be directly linked to Ab2 responses. The association of thrombotic events with some erectile dysfunction treatments in young women and the etiologic role of anti–platelet factor 4–polyanion antibodies may be the result of the adenoviral vector. However, the reported occurrence of myocarditis after treatment administration bears striking similarities to the myocarditis associated with Ab2 antibodies induced after some viral s.6 Ab2 antibodies could also mediate neurologic effects of erectile dysfunction or treatments, given the expression of ACE2 on neuronal tissues, the specific neuropathologic effects of erectile dysfunction ,11 and the similarity of these effects to Ab2-mediated neurologic effects does viagra make your dick bigger observed in other viral models.It would therefore be prudent to fully characterize all antibody and T-cell responses to the viagra and the treatments, including Ab2 responses over time.

Using huACE2 transgenic mice and crossing them with strains that are predisposed to autoimmunity or other human pathologic conditions can also provide important insights. An understanding of potential Ab2 responses may also provide insights into Ab1 maintenance and efficacy and into the application of antibody-based therapeutic agents. However, much more basic science research is needed to determine the potential role idiotype-based immunoregulation of both humoral and cell-mediated responses may play both in antiviral efficacy and in unwanted side effects of both erectile dysfunction and the treatments that protect us from it..

To the online viagra cost http://desertbellarosa.com/can-you-buy-ventolin-over-the-counter-in-usa/ Editor. Qatar had a first wave of s with severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) from March through June 2020, after which approximately 40% online viagra cost of the population had detectable antibodies against erectile dysfunction. The country subsequently had two back-to-back waves from January through May 2021, triggered by the introduction of the B.1.1.7 (or alpha) and B.1.351 (or beta) variants.1 This created an epidemiologic opportunity to assess res.

Using national, federated databases that have captured all erectile dysfunction–related data since the onset online viagra cost of the viagra (Section S1 in the Supplementary Appendix, available with the full text of this letter at NEJM.org), we investigated the risk of severe disease (leading to acute care hospitalization), critical disease (leading to hospitalization in an intensive care unit [ICU]), and fatal disease caused by res as compared with primary s in the national cohort of 353,326 persons with polymerase-chain-reaction (PCR)–confirmed between February 28, 2020, and April 28, 2021, after exclusion of 87,547 persons with a vaccination record. Primary was defined as the first PCR-positive swab. Re was online viagra cost defined as the first PCR-positive swab obtained at least 90 days after the primary .

Persons with re were matched to those with primary in a 1:5 ratio according to sex, 5-year age group, nationality, and calendar week of the PCR test date (Fig. S1 and online viagra cost Table S1 in the Supplementary Appendix). Classification of severe, critical, and fatal erectile dysfunction treatment followed World Health Organization guidelines, and assessments were made by trained medical personnel through individual online viagra cost chart reviews.

Table 1. Table 1 online viagra cost. Severity of erectile dysfunction Res as Compared with Primary s in the Population of Qatar.

Of 1304 identified res, 413 (31.7%) were caused by the B.1.351 variant, 57 (4.4%) by the B.1.1.7 variant, 213 (16.3%) by “wild-type” viagra, and 621 (47.6%) were of unknown status (Section S1 in online viagra cost the Supplementary Appendix). For reinfected persons, the median time between first and re was 277 days (interquartile range, 179 to 315). The odds online viagra cost of severe disease at re were 0.12 times (95% confidence interval [CI], 0.03 to 0.31) that at primary (Table 1).

There were no cases of critical disease at re and 28 cases at primary (Table S3), for an odds ratio of 0.00 (95% CI, 0.00 to 0.64) online viagra cost. There were no cases of death from erectile dysfunction treatment at re and 7 cases at primary , resulting in an odds ratio of 0.00 (95% CI, 0.00 to 2.57). The odds of online viagra cost the composite outcome of severe, critical, or fatal disease at re were 0.10 times (95% CI, 0.03 to 0.25) that at primary .

Sensitivity analyses were consistent with these results (Table S2). Res had 90% lower odds online viagra cost of resulting in hospitalization or death than primary s. Four res were severe enough to lead to acute care hospitalization.

None led online viagra cost to hospitalization in an ICU, and none ended in death. Res were rare and were generally mild, perhaps because of the online viagra cost primed immune system after primary . In earlier studies, we assessed the efficacy of previous natural as protection against re with erectile dysfunction2,3 as being 85% or greater.

Accordingly, for a person who has already had a primary , the risk online viagra cost of having a severe re is only approximately 1% of the risk of a previously uninfected person having a severe primary . It needs to be determined whether such protection against severe disease at re lasts for a longer period, analogous to the immunity that develops against other seasonal “common-cold” erectile dysfunctiones,4 which elicit short-term immunity against mild re but longer-term immunity against more severe illness with re. If this were the case with erectile dysfunction, the viagra (or at least the variants studied to date) could adopt a more benign pattern of when online viagra cost it becomes endemic.4 Laith J.

Abu-Raddad, Ph.D.Hiam Chemaitelly, M.Sc.Weill Cornell Medicine–Qatar, Doha, Qatar [email protected]Roberto Bertollini, M.D., M.P.H.Ministry of Public Health, Doha, Qatarfor the National Study Group for erectile dysfunction treatment Epidemiology Supported by the Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core at Weill Cornell Medicine–Qatar. The Ministry online viagra cost of Public Health. Hamad Medical online viagra cost Corporation.

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This letter was published on November 24, online viagra cost 2021, at NEJM.org. Members of the National Study Group for erectile dysfunction treatment Epidemiology are listed in the Supplementary Appendix, available with the full text of this letter at NEJM.org. 4 References1 online viagra cost.

Abu-Raddad LJ, Chemaitelly online viagra cost H, Butt AA. Effectiveness of the BNT162b2 erectile dysfunction treatment against the B.1.1.7 and B.1.351 variants. N Engl online viagra cost J Med 2021;385:187-189.2.

Abu-Raddad LJ, Chemaitelly H, Coyle P, et al. erectile dysfunction antibody-positivity protects online viagra cost against re for at least seven months with 95% efficacy. EClinicalMedicine 2021;35:100861-100861.3.

Abu-Raddad LJ, Chemaitelly H, online viagra cost Malek JA, et al. Assessment of the risk of severe acute respiratory syndrome online viagra cost erectile dysfunction 2 (erectile dysfunction) re in an intense reexposure setting. Clin Infect Dis 2021;73(7):e1830-e1840.4.

Lavine JS, Bjornstad ON, Antia online viagra cost R. Immunological characteristics govern the transition of erectile dysfunction treatment to endemicity. Science 2021;371:741-745.10.1056/NEJMc2108120-t1Table online viagra cost 1.

Severity of erectile dysfunction Res as Compared with Primary s in the Population of Qatar. Disease Outcome*Re†Primary †Odds Ratio online viagra cost (95% CI)no. Of persons online viagra cost with outcome/no.

Of persons with that was not severe, critical, or fatalSevere disease4/1300158/60950.12 (0.03–0.31)Critical disease0/130028/60950.00 (0.00–0.64)Fatal disease0/13007/60950.00 (0.00–2.57)Severe, critical, or fatal disease4/1300193/60950.10 (0.03–0.25)The Clinical Implications of Basic Research series has focused on highlighting laboratory research that could lead to advances in clinical therapeutics. However, the path between the laboratory and online viagra cost the bedside runs both ways. Clinical observations often pose new questions for laboratory investigations that then lead back to the clinic.

One of a series of occasional articles drawing attention to the bedside-to-bench flow of information is presented here, under the Basic Implications of Clinical Observations online viagra cost rubric. We hope our readers will enjoy these stories of discovery, and we invite them to submit their own examples of clinical findings that have led to insights in basic science. The pathogenesis of severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) is incompletely understood, with its effects on multiple organ systems1 and the syndrome of “long erectile dysfunction treatment” occurring long after the resolution of .2 The development of multiple efficacious treatments has been critical in the control of the viagra, but their efficacy has been limited online viagra cost by the appearance of viral variants, and the treatments can be associated with rare off-target or toxic effects, including allergic reactions, myocarditis, and immune-mediated thrombosis and thrombocytopenia in some healthy adults.

Many of these phenomena are likely to be immune-mediated.3 How can we understand this diversity in immune online viagra cost responses in different persons?. Figure 1. Figure 1 online viagra cost.

Anti-idiotype Antibodies and erectile dysfunction. Both severe online viagra cost acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) and the treatments against it elicit antibodies to the spike protein that the viagra uses to bind to the angiotensin-converting–enzyme 2 (ACE2) receptor on target cells. The receptor is widely expressed.

These antibodies are called online viagra cost Ab1. The idiotype portions of Ab1 that bind and neutralize the spike protein have distinctive sequences in complementarity-determining region online viagra cost 3 (CDR3), and those antibody-binding regions can themselves elicit antibody responses called anti-idiotype (Ab2) antibodies as a means of down-regulation. Ab2 antibodies can act in several ways.

They can bind to the protective neutralizing Ab1 antibody, resulting online viagra cost in immune-complex formation and clearance, thus impairing Ab1 efficacy. Some of the Ab2 binding regions, or paratopes, can also mirror the spike protein itself and bind to the same target as the spike protein, the ACE2 receptor. That binding could, in theory, exert several different — but not necessarily mutually exclusive — effects on the cell, depending on the nature of online viagra cost the Ab2 antibodies and the role of the receptors in the cell.

For example, it could potentially block ACE2 function by competitively inhibiting normal ligand interactions. Alternatively, it could stimulate ACE2 function by triggering the receptor, affect expression of ACE2 after binding by down-regulating or internalizing ACE2, or, after binding the cells, induce a complement-mediated or immune-cell attack on ACE2-expressing cells.One way of thinking about online viagra cost the complexity of the immune response is through the lens of anti-idiotype immune responses. The Network Hypothesis, formulated in 1974 by Niels online viagra cost Jerne, described a mechanism by which the antibody responses to an antigen themselves induced downstream antibody responses against the antigen-specific antibody.4 Every antibody that is induced and specific for an antigen (termed “Ab1” antibody) has immunogenic regions, particularly in their variable-region antigen-binding domains, that are unique as a result of genetic recombination of immunoglobulin variable, diversity, and joining (VDJ) genes.

VDJ recombination results in new and therefore immunogenic amino acid sequences called idiotopes, which are then capable of inducing specific antibodies against Ab1 antibodies as a form of down-regulation. A similar paradigm has been proposed for online viagra cost T cells. However, these regulatory immune responses are also capable of doing much more.

The paratopes, or antigen-binding online viagra cost domains, of some of the resulting anti-idiotype (or “Ab2”) antibodies that are specific for Ab1 can structurally resemble that of the original antigens themselves. Thus, the Ab2 antigen-binding region can potentially represent an exact mirror image of the initial targeted antigen in the Ab1 response, and Ab2 antibodies have even been examined for potential use as a surrogate for the antigen in treatment studies. However, as a result of this mimicry, Ab2 antibodies also have online viagra cost the potential to bind the same receptor that the original antigen was targeting (Figure 1).

Ab2 antibodies binding to the original receptor on normal cells therefore have the potential to mediate profound effects on the cell that could result in pathologic changes, particularly in the long term — long after the original antigen itself has disappeared.This aspect of regulation of immune-cell responses was postulated by Plotz in 1983 as a online viagra cost possible cause of autoimmunity arising after viral 5 and has since been supported experimentally by direct transfer of anti-idiotype antibodies. Ab2 antibodies generated against the enteroviagra coxsackieviagra B3 in mice can bind myocyte antigens, resulting in autoimmune myocarditis,6 and anti-idiotype responses can act as acetylcholine receptor agonists, leading to myasthenia gravis symptoms in rabbits.7 In addition, by displaying the mirror image of the viral antigen, Ab2 alone can even mimic the deleterious effects of the viagra particle itself, as has been shown with bovine viral diarrhea viagra antigen.8For erectile dysfunction , attention centers on the spike (S) protein and its critical use of the angiotensin-converting–enzyme 2 (ACE2) receptor to gain entry into the cell. Given its critical role in regulating angiotensin responses, many physiological effects can be influenced by ACE2 engagement.9 The S protein itself has a direct effect on suppressing ACE2 signaling by a variety of mechanisms and can also directly trigger toll-like receptors and online viagra cost induce inflammatory cytokines.10 Anti-idiotype responses may affect ACE2 function, resulting in similar effects.

However, preclinical and clinical assessments of antibody responses to erectile dysfunction treatments have focused solely on Ab1 responses and viagra-neutralizing efficacy. The delineation of potential anti-idiotype responses has inherent difficulties because of the polyclonal nature of responses, dynamic kinetics, and the online viagra cost concurrent presence of both Ab1 and Ab2 antibodies. Furthermore, ACE2 expression within cells and tissues can be variable.

The different treatment constructs (RNA, DNA, adenoviral, and protein) are also likely to have online viagra cost differential effects on Ab2 induction or in the mediation of treatment effects that differ from responses to . Some off-target effects online viagra cost may not be directly linked to Ab2 responses. The association of thrombotic events with some erectile dysfunction treatments in young women and the etiologic role of anti–platelet factor 4–polyanion antibodies may be the result of the adenoviral vector.

However, the reported occurrence of myocarditis after treatment online viagra cost administration bears striking similarities to the myocarditis associated with Ab2 antibodies induced after some viral s.6 Ab2 antibodies could also mediate neurologic effects of erectile dysfunction or treatments, given the expression of ACE2 on neuronal tissues, the specific neuropathologic effects of erectile dysfunction ,11 and the similarity of these effects to Ab2-mediated neurologic effects observed in other viral models.It would therefore be prudent to fully characterize all antibody and T-cell responses to the viagra and the treatments, including Ab2 responses over time. Using huACE2 transgenic mice and crossing them with strains that are predisposed to autoimmunity or other human pathologic conditions can also provide important insights. An understanding of potential Ab2 responses may also provide insights into Ab1 maintenance and efficacy and into the application online viagra cost of antibody-based therapeutic agents.

However, much more basic science research is needed to determine the potential role idiotype-based immunoregulation of both humoral and cell-mediated responses may play both in antiviral efficacy and in unwanted side effects of both erectile dysfunction and the treatments that protect us from it..

Viagra essential oil

21 July 2021 The IBMS supports a new report by Roche that calls for greater investments for diagnostic services within the NHS viagra essential oil. Roche has released a new report, The Future of Diagnostics Delivery in the UK, which highlights a current gap between the high value of diagnostic services and the investment these services currently receive within the NHS. Among other key findings, the report states that while 95% of all clinical pathways rely on patient access to pathology services, funding for pathology only accounts for 2% of the current NHS budget.

The IBMS often informs that biomedical scientists are responsible for over 70% of all diagnosis viagra essential oil and carry out over one billion tests a year within the NHS. Roche’s report emphasises there must be adequate investment in future diagnostic services in order for our profession to continue carrying out its central role at the heart of healthcare. IBMS Chief Executive David Wells shared his support of Roche’s report.

"Now is the time to be thinking about the future of diagnostics viagra essential oil. As the UK sector expands, we must ensure that the workforce is highly skilled and regulated, that the diagnostic industry, new and existing laboratories and testing streams ensure world class quality and safety and, most importantly, that we continue to supply education and training opportunities for the pipeline of future scientists. If we get this right and expand efficiently, we will become a global leader that can deliver on all the care and testing that all our citizens need - with enough expertise and infrastructure left over for innovation and discovery." The new report from Roche Diagnostics builds on work undertaken by partners in the sector, including an ABHI report published last year, and makes a series of important recommendations to inform the direction of diagnostics delivery in the UK.

These include viagra essential oil. Recommendations for strengthening the future of UK diagnostics and improving patient access to diagnostic innovations. Expanding the size and profile of the NHS pathology service.

Developing the future testing viagra essential oil landscape. And Increasing the uptake of innovative diagnostics across care pathways. Recommendations to inform the direction of diagnostics delivery in the UK The full recommendations of the NHS MedTech Funding Mandate should be implemented immediately to ensure that innovations that are both clinically and cost-effective are clearly commissioned and funded across the NHS, and then adopted by hospitals and commissioners.

The Government should undertake a major drive to expand viagra essential oil the pathology workforce, and greater focus must be given to support career development and education, through training, upskilling and apprenticeships. A new UK Diagnostics Coalition should be established to champion the work of both the pathology and diagnostic sectors. The erectile dysfunction treatment testing infrastructure should be integrated into NHS pathology services and repurposed to support screening of at-risk cohorts for early signs of other diseases.

A system-wide viagra essential oil approach to focus on outcomes rather than activity reimbursement should be adopted to drive uptake of diagnostic innovations. Geoff Twist, Managing Director, Roche Diagnostics (UK and Ireland), said. “From prevention to disease management, diagnostic testing has always been vital to patients and clinicians.

However, the erectile dysfunction treatment viagra has irrefutably viagra essential oil demonstrated the essential role that diagnostics plays in the health of every citizen in this country. Through effective collaboration we’ve shown that new diagnostic innovation can be developed and rolled out at speed across the NHS – and the significant benefit this has for patients. But innovation is only effective when it reaches the people who need it, which is why we need to build on this momentum and seize the unique opportunity to build a strong and sustainable UK diagnostics sector that is fit for the future.” Animation [embedded content] Downloads21 July 2021 We need members to come together to help protect the future of the profession This is a call out to our members to help sustain the pipeline of future biomedical scientists and specialist biomedical scientists by signing up to become a Registration Training Portfolio verifier or a Specialist Portfolio examiner (click for applications).If you are eligible, please think about taking on an active role in the development and nourishment of your profession.

Full guidance, training and support will be given and you will be providing a valuable viagra essential oil service to healthcare, as well as benefiting your own professional development. It refreshes your knowledge You become aware of different methodologies It provides new experiences and new ideas You develop new skills in peer review and assessment It creates networking opportunities It can refresh your CV by demonstrating active professional engagement Once you have submitted your application, click to sign up and join us on September 15th or November 10th for your virtual training session. The criteria for a successful application are.

IBMS Member or viagra essential oil Fellow Health and Care Professions Council (HCPC) registered A minimum of three years post registration experience Currently working in an IBMS-approved training laboratory Actively participating in CPD for at least the last two years. For more details visit ibms.org/education/verifiers-and-examiners or email us on registration@ibms.org (verifier) or specialistportoflio@ibms.org (examiner).It is always our goal to keep our qualifications as affordable and convenient for the profession as possible - helping you to progress in your career with relative ease. However, without more active verifiers and examiners coming forward, our current verification and assessment processes will be unsustainable.

Our only option would be to look at alternative measures that may not have the same flexibility that we currently have, and which could mean candidates would have to wait longer and travel further in order to complete their viagra essential oil qualifications, making it harder for our profession to flourish.Most of our assessments are now done remotely, saving travelling time and minimising disruption to our assessor and verifiers’ day, and where a visit is required we cover travel expenses and look to minimise the distance to be travelled. The current situation makes more sense - with the profession pooling together and volunteering to keep prices low for those who want to progress. For now, we would like to put the onus back onto our members and the profession - and hope that we can all continue to support and nourish our learners so that everybody can thrive.JOIN THE VITAL FEW.

21 July 2021 The IBMS http://cardozaartgallery.com/get-lasix-prescription/ supports online viagra cost a new report by Roche that calls for greater investments for diagnostic services within the NHS. Roche has released a new report, The Future of Diagnostics Delivery in the UK, which highlights a current gap between the high value of diagnostic services and the investment these services currently receive within the NHS. Among other key findings, the report states that while 95% of all clinical pathways rely on patient access to pathology services, funding for pathology only accounts for 2% of the current NHS budget. The IBMS often informs that biomedical scientists are responsible for online viagra cost over 70% of all diagnosis and carry out over one billion tests a year within the NHS.

Roche’s report emphasises there must be adequate investment in future diagnostic services in order for our profession to continue carrying out its central role at the heart of healthcare. IBMS Chief Executive David Wells shared his support of Roche’s report. "Now is the time to be thinking about online viagra cost the future of diagnostics. As the UK sector expands, we must ensure that the workforce is highly skilled and regulated, that the diagnostic industry, new and existing laboratories and testing streams ensure world class quality and safety and, most importantly, that we continue to supply education and training opportunities for the pipeline of future scientists.

If we get this right and expand efficiently, we will become a global leader that can deliver on all the care and testing that all our citizens need - with enough expertise and infrastructure left over for innovation and discovery." The new report from Roche Diagnostics builds on work undertaken by partners in the sector, including an ABHI report published last year, and makes a series of important recommendations to inform the direction of diagnostics delivery in the UK. These include online viagra cost. Recommendations for strengthening the future of UK diagnostics and improving patient access to diagnostic innovations. Expanding the size and profile of the NHS pathology service.

Developing online viagra cost the future testing landscape. And Increasing the uptake of innovative diagnostics across care pathways. Recommendations to inform the direction of diagnostics delivery in the UK The full recommendations of the NHS MedTech Funding Mandate should be implemented immediately to ensure that innovations that are both clinically and cost-effective are clearly commissioned and funded across the NHS, and then adopted by hospitals and commissioners. The Government online viagra cost should undertake a major drive to expand the pathology workforce, and greater focus must be given to support career development and education, through training, upskilling and apprenticeships.

A new UK Diagnostics Coalition should be established to champion the work of both the pathology and diagnostic sectors. The erectile dysfunction treatment testing infrastructure should be integrated into NHS pathology services and repurposed to support screening of at-risk cohorts for early signs of other diseases. A system-wide approach to focus on outcomes rather than online viagra cost activity reimbursement should be adopted to drive uptake of diagnostic innovations. Geoff Twist, Managing Director, Roche Diagnostics (UK and Ireland), said.

“From prevention to disease management, diagnostic testing has always been vital to patients and clinicians. However, the online viagra cost erectile dysfunction treatment viagra has irrefutably demonstrated the essential role that diagnostics plays in the health of every citizen in this country. Through effective collaboration we’ve shown that new diagnostic innovation can be developed and rolled out at speed across the NHS – and the significant benefit this has for patients. But innovation is only effective when it reaches the people who need it, which is why we need to build on this momentum and seize the unique opportunity to build a strong and sustainable UK diagnostics sector that is fit for the future.” Animation [embedded content] Downloads21 July 2021 We need members to come together to help protect the future of the profession This is a call out to our members to help sustain the pipeline of future biomedical scientists and specialist biomedical scientists by signing up to become a Registration Training Portfolio verifier or a Specialist Portfolio examiner (click for applications).If you are eligible, please think about taking on an active role in the development and nourishment of your profession.

Full guidance, training and support will be given and you will be providing a valuable service to healthcare, as well as benefiting your own professional development. It refreshes your knowledge You become aware of different methodologies It provides new experiences and new ideas You develop new skills in peer review and assessment It creates networking opportunities It can refresh your CV by demonstrating active professional engagement Once you have submitted your application, click to sign up and join us on September 15th or November 10th for your virtual training session. The criteria for a successful application are. IBMS Member or Fellow Health and Care Professions Council (HCPC) registered A minimum of three years post registration experience Currently working in an IBMS-approved training laboratory Actively participating in CPD for at least the last two years.

For more details visit ibms.org/education/verifiers-and-examiners or email us on registration@ibms.org (verifier) or specialistportoflio@ibms.org (examiner).It is always our goal to keep our qualifications as affordable and convenient for the profession as possible - helping you to progress in your career with relative ease. However, without more active verifiers and examiners coming forward, our current verification and assessment processes will be unsustainable. Our only option would be to look at alternative measures that may not have the same flexibility that we currently have, and which could mean candidates would have to wait longer and travel further in order to complete their qualifications, making it harder for our profession to flourish.Most of our assessments are now done remotely, saving travelling time and minimising disruption to our assessor and verifiers’ day, and where a visit is required we cover travel expenses and look to minimise the distance to be travelled. The current situation makes more sense - with the profession pooling together and volunteering to keep prices low for those who want to progress.

For now, we would like to put the onus back onto our members and the profession - and hope that we can all continue to support and nourish our learners so that everybody can thrive.JOIN THE VITAL FEW.

What is the active ingredient in viagra

Choice is probably one of what is the active ingredient in viagra the most often discussed areas in http://marykatwahl.com/how-to-order-cipro-online/ bioethics, alongside the related concepts of informed consent and autonomy. It is generally, prima facie, portrayed as what is the active ingredient in viagra a good thing. In healthcare, the 2000s saw the UK Prime Minister Tony Blair what is the active ingredient in viagra pursue the ‘Choice Agenda’ where, ‘As capacity expands, so choice will grow. Choice will fundamentally change the balance of power in the NHS.’1 In a consumerist society giving consumers more choice is seen as desirable.

However, choice what is the active ingredient in viagra is not a good in itself, giving people more choice in certain situations can be problematic. I.e. Consumerism drives economic growth and this has a detrimental effect on the environment. And increasing the range of choices a patient is offered is often not the best way to improve the quality of healthcare provision.2 The assumptions behind the valuing of choice need careful unpacking and this Issue of the Journal of Medical Ethics includes papers that explore choice in a number of areas.This Issue's Editor’s choice is Tom Walker’s ‘The Value of Choice’,3 which puts forward a suggestion for the importance of the symbolic value of choice.

There are a number of ways of categorising the value of choice in healthcare. One account sees choice as valuable because it is by choosing that individuals make their life their own. Another account sees choice as valuable for instrumental reasons, people are generally, assuming they are sufficiently informed, the best judge of their own best interests. Walker argues for an additional third reason, the symbolic value of choice, originally proposed by Scanlon.

This sees choice as valuable because being given the option to choose, whether or not one takes it up, not the act of choosing is what makes choice valuable. Being offered the option to choose has a ‘communicative role’ in that it communicates that the person has standing and, for certain types of choice, being denied the opportunity to choose, ‘can be both demeaning and stigmatising.’ Walker states that denying someone the opportunity to choose in certain circumstances does not communicate anything untoward, and he goes to explore how we might determine when not allowing someone a choice would be demeaning. Here he stresses the importance of context in making this determination, it is not fixed by the features of a patient, but what being ‘allowed’ or ‘denied’ the opportunity to make a choice reveals about the healthcare professional’s view of the patient. €˜It communicates that they either see those patients as competent and equal members of society, or that they do not.’ Denying a patient the opportunity to choose an ineffective treatment, for example, does not communicate a negative judgement.

Walker says his account, ‘is intended to supplement existing accounts, not replace them. Because choice is valuable for more than one reason no single account can capture everything that matters.’The importance of pointing to the context of the choice is highlighted in Walker’s paper and it is only through careful examination of the context of that offering that we can determine if, in fact, this is an area where choice should be offered and to whom. Such an examination is carried out in Cameron Beattie’s paper,4 which considers the High Court review of service provision at the youth-focussed gender identity Tavistock Clinic. Beattie disagrees with the High Court’s view that it is ’highly unlikely’ that under-13s, and ’doubtful’ that 14–15 years old, can be competent to consent to puberty blocker therapy for gender dysphoria.

Beattie argues that having puberty blocker therapy is a choice that minors should be given the opportunity to make. In principle, children of that age could be competent to make the decision and that the decision is no more complex than other medical decisions that Gillick competence has conventionally been applied to. Children of this age fall into what Walker calls a ‘transitional’ group, ‘Of particular importance here is the extent to which societal features mean members of some groups find it particularly hard to be recognised as competent and equal members of society. That includes members of groups subject to discrimination….It also includes those who are in what we might call transitional groups such as teenagers struggling to be recognised as competent.’ In the case of denying puberty blockers, the symbolic value of choice is clear.The paper by Zeljka Buturovic5 examines the debate over young childless women requesting sterilisation.

There has been a discussion in the literature that critiques doctors’ hesitancy to accede to this type of request and Buturovic argues against these criticisms. The argument is that rather than a doctor’s refusal to sterilise a young childless woman or putting up obstacles to this being examples of, variously, inconsistency, paternalism, pronatalist bias and discrimination, it is understandable that doctors should be reluctant to follow this unusual request, and such hesitancy is of potential benefit to the young woman. This hesitancy can act as a filter for women who are not seriously committed to sterilisation. This, in essence, is the opposite argument to Beattie’s paper, that the barriers put up to prevent people exercising their choice in this case are warranted.

Young childless women should have their choice scrutinised and if necessary delayed so that it can be ascertained if the choice is a genuine one, and ‘to weed out (the) confused and uncommitted.’ Ultimately, that choice should be available for young childless woman, but it is a choice, given its long-term consequences and likely lack of reversibility, that should be carefully considered.These papers show that choice is a contextually based, complex and multi-facetted concept and approaches such as Walker’s, give us tools to think more carefully about the value of choice and what that means in particular situations. A consideration of choice is not complete without thinking about the effects of our choices on others, and this needs to be at the forefront of any ethical analysis. The ‘choice-agenda’ can often be a proxy for an individualistic conception of personal responsibility and a construction of the ‘good’ of the choice as being solely about that individual’s right to exercise a choice, rather than a more nuanced consideration of the wider, or even limited, effects of that choice on others. Although we have well-worn ways of thinking about harm – harm to others and liberty limiting principles6 – how the exercising of individual choice might harm others is often debatable and unclear, and political with a small and large P!.

For instance, in July 2021 Boris Johnson, the UK prime minister, announced that mask wearing would now be one of personal choice. The government would end the legal obligation to wear a face covering, ‘We will move away from legal restrictions and allow people to make their own informed decisions about how to manage the viagra.’ Johnson went on to say. €˜Guidance will suggest where you might choose to do so - especially when cases are rising and where you come into contact with people you don't usually meet in enclosed spaces, such as obviously crowded public transport.’7 This mandate for ‘freedom-day’ was criticised in a number of letters in high ranking medical journals,8 9 arguing, ‘The narrative of “caution, vigilance, and personal responsibility” is an abdication of the government’s fundamental duty to protect public health. €œPersonal responsibility” does not work in the face of an airborne, highly contagious infectious disease.

Infectious diseases are a matter of collective, rather than individual, responsibility.’8 In this case, someone’s personal choice to not wear a mask on public transport, where social distancing is impossible, conflicts with someone else’s choice to travel to work as safely as they can. As the critics of this policy and work in public health ethics notes, one person’s choice can have a significant detrimental effect on others, and in situations like this, such as this mask wearing example, where not allowing choice, that is maintaining the legally mandated requirement to wear a face mask (unless there are reasons for an exemption), is an ethically acceptable restriction on ‘personal choice.’ In Walker’s terminology disallowing this choice it is not demeaning or stigmatising, as it applies to everyone, and does not fail to recognise any particular person or group as equal members of society.Choice is often portrayed as a good thing like parenthood and apple pie and the use of choice by politicians to whip up support and bolster their political agendas, as shown by the examples of Blair and Johnson, shows the rhetorical power of the concept. But to really address in what circumstances choices should be offered, to whom and what type of choice, we need theoretical tools to help us understand and be attentive to the wider implications and the papers in this Issue help us to do that.Ethics statementsPatient consent for publicationNot applicable.Ethics approvalThis study does not involve human participants.IntroductionLarge-scale, international data sharing opens the door to the study of so-called ‘Big Data’, which holds great promise for improving patient-centred care. Big Data health research is envisioned to take precision medicine to the next level through increased understanding of disease aetiology and phenotypes, treatment effects, disease management and healthcare expenditure.1 However, lack of public trust is proven to be detrimental to the goals of data sharing.2 The case of care.data in the UK offers a blatant example of a data sharing initiative gone awry.

Criticism predominantly focused on limited public awareness and lack of clarity on the goals of the programme and ways to opt out.3 Citizens are becoming increasingly aware and critical of data privacy issues, and this warrants renewed investments to maintain public trust in data-intensive health research. Here, we use the term data-intensive health research to refer to a practice of grand-scale capture, (re)use and/or linkage of a wide variety of health-related data on individuals.Within the European Union (EU), the recently adopted General Data Protection Regulation (GDPR) (EU 2016/679) addresses some of the concerns the public may have with respect to privacy and data protection. One of the primary goals of the GDPR is to give individuals control over their personal data, most notably through consent.4 Other lawful grounds for the processing of personal data are listed, but it is unclear how these would exactly apply to scientific research. Legal norms remain open to interpretation and thus offer limited guidance to researchers.5 6 In Recital 33, the GDPR actually mentions that additional ethical standards are necessary for the processing of personal data for scientific research.

This indicates a recognised need for entities undertaking activities likely to incite public unease to go beyond compliance with legal requirements.7 Complementary ethical governance then becomes a prerequisite for securing public trust in data-intensive health research.A concept that could be of use in developing ethical governance is that of a ‘social license to operate’.7 The social license captures the notion of a mandate granted by society to certain occupational groups to determine for themselves what constitutes proper conduct, under the condition that such conduct is in line with society’s expectations. The term ‘social license’ was first used in the 1950s by American sociologist Everett Hughes to address relations between professional occupations and society.8 The concept has been used since to frame, for example, corporate social responsibility in the mining industry,9 governance of medical research in general8 and of data-intensive health research more specifically.7 10 As such, adequate ethical governance then becomes a precondition for obtaining a social license for data sharing activities.Key to an informed understanding of the social license is identifying the expectations society may hold with regard to sharing of and access to health data. Here, relevant societal actors are the subjects of Big Data health research, constituting both patients and the general public. Identification of patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework.

We know of the existence of research papers that have captured these views using quantitative or qualitative methods or a combination of both. So far, systematic reviews of the literature have limited their scope to citizens of specific countries,11 12 qualitative studies only13 or the sharing of genomic data.14 Therefore, we performed an up-to-date narrative review of both quantitative and qualitative studies to explore predominant patient and public views and attitudes towards data sharing for health research.MethodsWe searched the literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar in April 2019 for publications addressing patients’ and public views and attitudes towards the use of health data for research purposes. Synonyms of the following terms (connected by ‘AND’) were used to search titles and/or abstracts of indexed references. Patient or public.

Views. Data sharing. Research (See box 1 and online supplementary appendix 1). To merit inclusion, an article had to report results from an original research study (qualitative, quantitative or mixed methods) on attitudes of individuals regarding use of data for health research.

We restricted eligibility to records published in English and studies performed between 2009 and 2019. We chose 2009 as a lower limit because we assume that patients’ and public perspectives might have changed substantially with increasing awareness and use of digital (health) technologies. Systematic reviews and meta-analyses synthesising the empirical literature on this topic also qualified for review. Reports from stakeholder meet-ups and workshops were eligible as long as they included patients or the public as participants.

Since we were only interested in empirical evidence, expert opinion and publications merely advocating for the inclusion of patients’ and public views in Big Data health research were excluded. Studies that predominantly reported on views of other stakeholders—such as clinicians, researchers, policy makers or industry—were excluded. Articles reporting on conference proceedings, or views regarding (demographic) data collection in low or middle income countries or for public health and care/quality improvement were not considered relevant to this review. Despite our specific interest in data sharing within the European context, we broadened eligibility criteria to include studies performed in the USA, Canada, Australia and New Zealand.

Additional articles were identified through consultation with experts and review of references in the manuscript identified through the literature database searches. Views and attitudes of patients and the public were identified from selected references and reviewed by means of thematic content analysis.Supplemental materialBox 1 Key search terms(patient* OR public OR citizen*)AND(attitude* OR view* OR perspective* OR opinion* OR interview* OR qualitative* OR questionnaire* OR survey*)AND(“data sharing” OR “data access” OR “data transfer”)ANDResearchResultsStudy characteristicsSearches in PubMed (MEDLINE), Embase, Scopus and Google Scholar resulted in a total of 1153 non-unique records (see online supplementary appendix 1). We identified 27 papers for review, including 12 survey or questionnaire studies (quantitative), 8 interview or focus group studies (qualitative), 1 mixed methods study and 6 systematic reviews (see table 1). Most records were excluded because they were not relevant to our research question or because they did not report on findings from original (empirical) research studies.

Ten studies reported on views of patients, 11 on views of the public/citizens and 6 studies combined views of patients, research participants and the public.View this table:Table 1 Study characteristicsWillingness to share data for health researchReviewed papers suggest widespread support for the sharing of data for health research.Four systematic reviews synthesising the views of patients and the public report that willingness for data to be linked and shared for research purposes is high11–14 and that people are generally open to and understand the benefits of data sharing.15Outpatients from a German university hospital who participated in a questionnaire study (n=503) expressed a strong willingness (93%) to give broad consent for secondary use of data,16 and 93% of a sample of UK citizens with Parkinson’s disease (n=306) were willing to share their data.17 Wide support for sharing of data internationally18 19 and in multicentre studies20 was reported among patient participants. Goodman et al found that most participants in a sample of US patients with cancer (n=228) were willing to have their data made available for ‘as many research studies as possible’.21 Regarding the use of anonymised healthcare data for research purposes, a qualitative study found UK rheumatology patients and patient representatives in support of data sharing (n=40).22Public respondents in survey studies recognised the benefits of storing electronic health information,23 and 78.8% (n=151) of surveyed Canadians felt positive about the use of routinely collected data for health research.24 The majority (55%) of a sample of older Swiss citizens (n=40) were in favour of placing genetic data at disposal for research.25 Focus group discussions convened in the UK showed that just over 50% of the members of the Citizens Council of The National Institute for Health and Care Excellence (NICE) said they would have no concerns about NICE using anonymised data derived from personal care records to evaluate treatments,26 and all participants in one qualitative study were keen to contribute to the National Healthcare Service (NHS)-related research.27Motivations to share dataPatients and public participants expressed similar reasons and motivations for their willingness to share data for health research, including contributing to advancements in healthcare, returning incurred benefits and the hope of future personal health benefits (tables 2–4).View this table:Table 2 Patients’ views and attitudes towards the sharing of health data for researchView this table:Table 3 Public views and attitudes towards the sharing of health data for researchView this table:Table 4 Patients’ and public views and attitudes towards the sharing of health data for researchIn the two systematic reviews that addressed this topic, sharing data for ‘the common good’ or ‘the greater good’ was identified as one of the most prevalent motivations.12 14For patients specifically, to help future patients or people with similar health problems was an important reason.14 16 One survey study conducted among German outpatients found that 72% listed returning their own benefits incurred from research as a driver for sharing clinical data.16 Patients with rare disease were also motivated by ‘great hope and trust’ in the development of international databases for health research.19 Among patients, support of research in general,16 the value attached to answering ‘important’ research questions,20 and a desire to contribute to advancements in medicine14 were prevalent reasons in favour of data sharing. Ultimately, the belief that data sharing could lead to improvements in health outcome and care was reported.20Only one original study research paper addressed public motivations. This study found that older citizens mentioned auistic reasons and the greater good in a series of interviews as reasons to share genetic data for research.25 In these interviews, citizens expressed no expectations of an immediate impact or beneficial return but ultimately wanted to help the next generation.Perceived benefits of data sharingPatients and the public perceive that data sharing could lead to better patient care through improved diagnosis and treatment options and more efficient use of resources.

Patients seem to also value the potential of (direct) personal health benefits.Two systematic reviews reported on perceived benefits of data sharing for health research purposes. Howe et al mentioned perceived benefits to research participants or the immediate community, benefits to the public and benefits to research and science.15 Shabani et al also listed accelerating research advancement and maximising the value of resources as perceived benefits.14Surveyed patients perceived that data sharing could help their doctor ‘make better decisions’ about their health (94%, n=3516)28 or result in an increased chance of receiving personalised health information (n=228).21In the original studies reviewed, advantages and potential benefits of data sharing were generally recognised by public and patient participants.22 29 Data sharing was believed to enable the study of long-term treatment effects and rare events, as well as the study of large numbers of people,24 to improve diagnosis25 and treatment quality,20 23 as well as to stimulate innovation30 and identify new treatment options.25 A cross-sectional online survey among patient and citizen groups in Italy (n=280) also identified the perception that data sharing could reduce waste in research.30Perceived risks of data sharingThe most significant risks of data sharing were perceived to results from breaches of confidentiality, commercial use and potential abuse of the data.Systematic reviews report on patients’ and public concerns about confidentiality in general,13 15 sometimes linked to the risk of reidentification,14 concerns about a party's competence in keeping data secure,12 and concerns that personal information could be mined from genomic data.14 A systematic review by Stockdale et al identified concerns among the public (UK and Ireland) about the motivation a party might have to use the data.14Patients in a UK qualitative study (n=40) perceived ‘detrimental’ consequences of data ‘falling into the wrong hands’, such as insurance companies.22 Respondents from the online patient community PatientsLikeMe were fearful of health data being ‘stolen by hackers’ (87%, n=3516).28Original research studies flagged data security and privacy as major public concerns.16 18 20 25 26 29–32 More specifically, many studies found that participants worried about who would have access to the data and about risk of misuses or abuses.13 15 18 25 27 33 A large pan-European survey among respondents from 27 EU member states revealed public concerns about different levels of access by third parties (48.9%–60.6%, n=20 882).23 Overall, reviewed papers suggest that patients and the public are concerned about the use of their data for commercial purposes.14 27 For example, the NICE Citizens Council expressed concerns about the potential for data to be sold to other organisations and used for profit and for purposes other than research.26 The Citizens Council also highlighted the need for transparency about how data are used and how it might be used in the future and for ensuring the research is conducted according to good scientific practice and that data are used to benefit society. Concerns about control and ownership of data were identified13 33 and about re-use of data for purposes that participants do not agree on.30 Fear of discrimination, stigmatisation, exploitation or other repercussions as a consequence of data being shared was widely cited by individuals.14 15 18Barriers to share dataStudies showed that patients and the public rarely mention barriers to data sharing in absolute terms. Rather, acceptance seemed to decrease if data sharing was financially motivated, and if people did not know how and with whom their data would be shared.First, individuals often opposed data sharing if it was motivated by financial gain or profit20 or if the data were shared with commercial/private companies.14 15 In one large pan-European survey (n=20 882), respondents were found to be strongly averse to health insurance companies and private sector pharmaceutical companies viewing their data.23 Second, lack of understanding and awareness around the use of data was viewed as a barrier to data sharing.15 22 Third, lack of transparency and controllability in releasing data were mentioned as factors compromising public trust in data sharing activities.14 22Factors affecting willingness to share dataA wide range of factors were identified from the literature that impacted individuals’ willingness to share data for health research, including geographical factors, age, individual-specific and research-specific characteristics.Geographical factorsMcCormack et al found that European patients’ expressions of trust and attitudes to risk were often affected by the regulatory and cultural practices in their home countries, as well as by the nature of the (rare) disease the patient participant had.18 Shah et al conducted a survey among patients in four Northern European countries (n=855) and found a significant association between country and attitudes towards sharing of deidentified data.34 Interestingly, Dutch respondents were less likely to support sharing of their deidentified data compared with UK citizens.AgeAmong a sample of surveyed patients with Parkinson’s disease (UK), a significant association was found between higher age and increased support for data sharing.17 According to a study based on semistructured interviews with older Swiss citizens, generational differences impacted willingness to share.25 With respect to public attitudes towards data sharing, findings of one systematic review suggest that males and older people are more likely to consent to sharing their medical data.27 A systematic review by Shabani et al suggests that patient and public participants with higher mean age are substantially less worried about privacy and confidentiality than other groups.14Individual-specific characteristicsA systematic review into patients’ and public perspectives on data sharing in the USA suggests that individuals from under-represented minorities are less willing to share data.11 A large multisite survey (n=13 000) among the US public found that willingness to share was associated with self-identified white race, higher educational attainment and lower religiosity.31 In another systematic review, race, gender, age, marital status and/or educational level all seemed to influence how people perceived sensitivity of genomic data and the sharing thereof.14 However, a UK study among patients with Parkinson’s disease found no clear relationship between data sharing and the number of years diagnosed, sex, medication class or health confidence.17Factors that clearly positively affected attitudes towards data sharing were perceptions of the (public) benefits and value of the research,13 20 fewer concerns and fewer information needs,31 and higher trust in and reputation of individuals or organisations conducting and/or overseeing data sharing.12–14 35 Conversely, willingness decreased with higher privacy and confidentiality concerns11 and higher distrust of the government as an oversight body for (genetic) research data.35Research-specific characteristicsPrivacy measures increased people’s willingness to share their data for health research, such as removal of social security numbers (90%, n=3516) and insurance ID (82%, n=3516), the sharing of only summary-level or aggregate data20 and deposition of data in a restricted access online database.29 Expressions of having control over what data are shared and with whom positively affected attitudes towards data sharing.34 In one study, being asked for consent for each study made participants (81%) feel ‘respected and involved’, and 74% agreed that they would feel that they ‘had control’.14 With respect to data sharing without prospective consent, participants became more accepting after being given information about the research processes and selection bias.27 Less support was observed for data sharing due to financial incentives25 and, more specifically, if data would be shared with private companies, such as insurance or pharmaceutical companies.11 25Conditions for sharingWidespread willingness to share data for health research very rarely led to participants’ unconditional support.

Studies showed agreement on the following conditions for responsible data sharing. Value, privacy, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.ValueOne systematic review found that participants found it important that the research as a result of data sharing should be in the public’s interest and should reflect participants’ values.15 The NICE Citizens Council advocated for appropriate systems and good working practices to ensure a consistent approach to research planning, data capture and analysis.26Privacy, risks and data securityThe need to protect individuals’ privacy was considered paramount11 14 21 34 and participants often viewed deidentification of personal data as a top privacy measure.11 24 30 36 One survey among US patients with cancer found that only 20% (n=228) of participants found linkage of individuals with their deidentified data acceptable for return of individual health results and to support further research.21 Secured access to databases was considered an important measure to ensure data security in data sharing activities.30 34 A systematic review of participants’ attitudes towards data sharing showed that people established risk minimisation as another condition for data sharing.15 Findings by Mazor et al suggest that patients only support studies that offer value and minimise security risks.20Transparency and controlConditions regarding transparency were information about how data will be shared and with whom,14 35 the type of research that is to be performed, by whom the research will be performed,16 information on data sharing and monitoring policies and database governance,35 conditions framing access to data and data access agreements,24 28 30 and any partnerships with the pharmaceutical industry.19 More generally, participants expressed the desire to be involved in the data sharing process,35 to be notified when their data are (re)used and to be informed of the results of studies using their data.15 Spencer et al identified use of an electronic interface as a highly valued means to enable greater control over consent choices.22 When asked about the use of personal data for health research by the NHS, UK citizens were typically willing to accept models of consent other than the ones they would prefer.37 Acceptance of consent models with lower levels of individual control was found to be dependent on a number of factors, including adequate transparency, control over detrimental use and commercialisation, and the ability to object, particularly to any processing considered to be inappropriate or particularly sensitive.37Information and trustOne systematic review identified trust in the ability of the original institution to carry out the oversight tasks as a major condition for responsible data sharing.14 Appropriate education and information about data sharing was thought to include public campaigns to inform stakeholders about Big Data32 and information communicated at open days of research institutions (such as NICE) to ensure people understand what their data are being used for and to reassure them that personal data will not be passed on or sold to other organisations.26 The informed consent process for study participation was believed to include information about the fact that individuals’ data could potentially be shared,15 30 the objectives of data sharing and (biobank) research, the study’s data sharing plans,29 governance structure, logistics and accountability.33Responsibility and accountabilityParticipants often placed the responsibility for data sharing practices on the shoulders of researchers. Secondary use of data collected earlier for scientific research was viewed to require a data access committee that involves a researcher from the original research project, a clinician, patient representative and a participant in the original study.36 Researchers of the original study were required to monitor data used by other researchers.36 In terms of accountability, patient and public groups in Italy (n=280) placed high value on sanctions for misuse of data.30 Information on penalties or other consequences of a breach of protection or misuse was considered important by many.31 35DiscussionIn this study, we narratively reviewed 27 papers on patients’ and public views on and attitudes towards the use of health data for scientific research. Studies reported a widespread—though conditional—support for the linkage and sharing of data for health research.

The only outlier seems to be the finding that just over half (n=25) of the NICE Citizens Council answered ‘no’ to the question whether they had any concerns if NICE used anonymised data to fill in the gaps if NICE was not getting enough evidence in ‘the usual ways’.26 However, we hasten to point out that the question about willingness to share is different from the question whether people have concerns or not. In addition, after a 2-day discussion meeting Council members were perhaps more sensitised to the potential concerns regarding data sharing. Therefore, we suggest that the way and context within which questions are phrased may influence the answers people give.Overall, people expressed similar motivations to share their data, perceived similar benefits (despite some variation between patients and citizens), yet at the same time displayed a range of concerns, predominantly relating to confidentiality and data security, awareness about access and control, and potential harms resulting from these risks. Both patient and public participants conveyed that certain factors would increase or reduce their willingness to have their data shared.

For example, the presence of privacy-protecting measures (eg, data deidentification and the use of secured databases) seemed to increase willingness to share, as well as transparency and information about data sharing processes and responsibilities. The identified views and attitudes appeared to come together in the conditions stipulated by participants. Value, privacy and confidentiality, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.In our Introduction, we mentioned that identifying patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework. In other words, what work should our governance framework be doing in order to obtain a social license?.

This review urges researchers and institutions to address people’s diverse concerns and to make an effort to meet the conditions identified. Without these conditions, institutions lack trustworthiness, which is vital for the proceedings of medicine and biomedical science. As such, a social license is not a ‘nice to have’ but a ‘need to have’. Our results also confirm that patients and the public indeed care about more than legal compliance alone, and wish to be engaged through information, transparency and control.

This work supports the findings of a recent systematic review into ethical principles of data sharing as specified in various international ethical guidelines and literature.38 What this body of research implies is considerable diversity of values and beliefs both between and within countries.The goal of this narrative review was to identify the most internationally dominant, aggregated patient and public views about the broad topic of data sharing for health research. We deliberately opted for the methodology of a narrative review rather than a systematic review. Most narrative reviews deal with a broad range of issues to a given topic rather than addressing a particular topic in depth.39 This means narrative reviews may be most useful for obtaining a broad perspective on a topic, and that they often are less useful in generating quantitative answers to specific clinical questions. However, because narrative reviews do not require specification of the search and selection strategy and the way of critically appraising literature can be variable, the connection between evidence generated by narrative reviews and (clinical) recommendations is less rigorous and risk of bias exists.

This is something to take into account in this study. A risk of bias assessment was not possible due to the heterogeneity of the findings. We acknowledge that our methodological choices may have affected the discriminative power or granularity of our findings. For example, there is a difference between sharing of routinely collected health data versus secondary use of health data collected for research purposes.

And we can only make loose assumptions about potential differences between patient and public views.In addition, we should mention that this work is centred around studies conducted in Western countries as the whole Big Data space and literature is dominated by Western countries, higher socioeconomic status and Caucasians. However, most of the disease burden globally and within countries is most probably not represented in the ‘Big Data’ and so we have to stress the lack of generalisability to large parts of the world.Nevertheless, we believe our findings point towards essential elements of a governance framework for data sharing for health research purposes. If we are to conclude that the identified conditions ought to act as the pillars of a governance framework, the next step is to identify how these conditions could be practically operationalised. For example, if people value information, transparency and control, what type of consent is most likely to valorise these conditions?.

And what policy for returning research results would be desirable?. Once we know what to value, we can start thinking about the ways to acknowledge that value. A new challenge arising here, however, is what to do when people hold different or even conflicting values or preferences. Discrete choice experiments could help to test people’s preferences regarding specific topics, such as preferred modes of informed consent.

Apart from empirical work, conceptual analysis is needed to clarify how public trust, trustworthiness of institutions and accountability are interconnected.ConclusionThis narrative review suggests widespread—though conditional—support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of health research, they report a number of significant concerns and related conditions. We believe identified conditions (eg, social value, data security, transparency and accountability) ought to be operationalised in a value-based governance framework that incorporates the diverse patient and public values, needs and interests, and which reflects the way these same conditions are met, to strengthen the social license for Big Data health research.Ethics statementsPatient consent for publicationNot required.AcknowledgmentsWe thank Susanne Løgstrup (European Heart Network) and Evert-Ben van Veen (Medlaw) for their valuable feedback during various stages in drafting the manuscript..

Choice is probably one of the most often discussed areas http://marykatwahl.com/how-to-order-cipro-online/ in online viagra cost bioethics, alongside the related concepts of informed consent and autonomy. It is generally, online viagra cost prima facie, portrayed as a good thing. In healthcare, the 2000s saw the UK Prime Minister Tony Blair pursue the ‘Choice online viagra cost Agenda’ where, ‘As capacity expands, so choice will grow. Choice will fundamentally change the balance of power in the NHS.’1 In a consumerist society giving consumers more choice is seen as desirable. However, choice is not a good online viagra cost in itself, giving people more choice in certain situations can be problematic.

I.e. Consumerism drives economic growth and this has a detrimental effect on the environment. And increasing the range of choices a patient is offered is often not the best way to improve the quality of healthcare provision.2 The assumptions behind the valuing of choice need careful unpacking and this Issue of the Journal of Medical Ethics includes papers that explore choice in a number of areas.This Issue's Editor’s choice is Tom Walker’s ‘The Value of Choice’,3 which puts forward a suggestion for the importance of the symbolic value of choice. There are a number of ways of categorising the value of choice in healthcare. One account sees choice as valuable because it is by choosing that individuals make their life their own.

Another account sees choice as valuable for instrumental reasons, people are generally, assuming they are sufficiently informed, the best judge of their own best interests. Walker argues for an additional third reason, the symbolic value of choice, originally proposed by Scanlon. This sees choice as valuable because being given the option to choose, whether or not one takes it up, not the act of choosing is what makes choice valuable. Being offered the option to choose has a ‘communicative role’ in that it communicates that the person has standing and, for certain types of choice, being denied the opportunity to choose, ‘can be both demeaning and stigmatising.’ Walker states that denying someone the opportunity to choose in certain circumstances does not communicate anything untoward, and he goes to explore how we might determine when not allowing someone a choice would be demeaning. Here he stresses the importance of context in making this determination, it is not fixed by the features of a patient, but what being ‘allowed’ or ‘denied’ the opportunity to make a choice reveals about the healthcare professional’s view of the patient.

€˜It communicates that they either see those patients as competent and equal members of society, or that they do not.’ Denying a patient the opportunity to choose an ineffective treatment, for example, does not communicate a negative judgement. Walker says his account, ‘is intended to supplement existing accounts, not replace them. Because choice is valuable for more than one reason no single account can capture everything that matters.’The importance of pointing to the context of the choice is highlighted in Walker’s paper and it is only through careful examination of the context of that offering that we can determine if, in fact, this is an area where choice should be offered and to whom. Such an examination is carried out in Cameron Beattie’s paper,4 which considers the High Court review of service provision at the youth-focussed gender identity Tavistock Clinic. Beattie disagrees with the High Court’s view that it is ’highly unlikely’ that under-13s, and ’doubtful’ that 14–15 years old, can be competent to consent to puberty blocker therapy for gender dysphoria.

Beattie argues that having puberty blocker therapy is a choice that minors should be given the opportunity to make. In principle, children of that age could be competent to make the decision and that the decision is no more complex than other medical decisions that Gillick competence has conventionally been applied to. Children of this age fall into what Walker calls a ‘transitional’ group, ‘Of particular importance here is the extent to which societal features mean members of some groups find it particularly hard to be recognised as competent and equal members of society. That includes members of groups subject to discrimination….It also includes those who are in what we might call transitional groups such as teenagers struggling to be recognised as competent.’ In the case of denying puberty blockers, the symbolic value of choice is clear.The paper by Zeljka Buturovic5 examines the debate over young childless women requesting sterilisation. There has been a discussion in the literature that critiques doctors’ hesitancy to accede to this type of request and Buturovic argues against these criticisms.

The argument is that rather than a doctor’s refusal to sterilise a young childless woman or putting up obstacles to this being examples of, variously, inconsistency, paternalism, pronatalist bias and discrimination, it is understandable that doctors should be reluctant to follow this unusual request, and such hesitancy is of potential benefit to the young woman. This hesitancy can act as a filter for women who are not seriously committed to sterilisation. This, in essence, is the opposite argument to Beattie’s paper, that the barriers put up to prevent people exercising their choice in this case are warranted. Young childless women should have their choice scrutinised and if necessary delayed so that it can be ascertained if the choice is a genuine one, and ‘to weed out (the) confused and uncommitted.’ Ultimately, that choice should be available for young childless woman, but it is a choice, given its long-term consequences and likely lack of reversibility, that should be carefully considered.These papers show that choice is a contextually based, complex and multi-facetted concept and approaches such as Walker’s, give us tools to think more carefully about the value of choice and what that means in particular situations. A consideration of choice is not complete without thinking about the effects of our choices on others, and this needs to be at the forefront of any ethical analysis.

The ‘choice-agenda’ can often be a proxy for an individualistic conception of personal responsibility and a construction of the ‘good’ of the choice as being solely about that individual’s right to exercise a choice, rather than a more nuanced consideration of the wider, or even limited, effects of that choice on others. Although we have well-worn ways of thinking about harm – harm to others and liberty limiting principles6 – how the exercising of individual choice might harm others is often debatable and unclear, and political with a small and large P!. For instance, in July 2021 Boris Johnson, the UK prime minister, announced that mask wearing would now be one of personal choice. The government would end the legal obligation to wear a face covering, ‘We will move away from legal restrictions and allow people to make their own informed decisions about how to manage the viagra.’ Johnson went on to say. €˜Guidance will suggest where you might choose to do so - especially when cases are rising and where you come into contact with people you don't usually meet in enclosed spaces, such as obviously crowded public transport.’7 This mandate for ‘freedom-day’ was criticised in a number of letters in high ranking medical journals,8 9 arguing, ‘The narrative of “caution, vigilance, and personal responsibility” is an abdication of the government’s fundamental duty to protect public health.

€œPersonal responsibility” does not work in the face of an airborne, highly contagious infectious disease. Infectious diseases are a matter of collective, rather than individual, responsibility.’8 In this case, someone’s personal choice to not wear a mask on public transport, where social distancing is impossible, conflicts with someone else’s choice to travel to work as safely as they can. As the critics of this policy and work in public health ethics notes, one person’s choice can have a significant detrimental effect on others, and in situations like this, such as this mask wearing example, where not allowing choice, that is maintaining the legally mandated requirement to wear a face mask (unless there are reasons for an exemption), is an ethically acceptable restriction on ‘personal choice.’ In Walker’s terminology disallowing this choice it is not demeaning or stigmatising, as it applies to everyone, and does not fail to recognise any particular person or group as equal members of society.Choice is often portrayed as a good thing like parenthood and apple pie and the use of choice by politicians to whip up support and bolster their political agendas, as shown by the examples of Blair and Johnson, shows the rhetorical power of the concept. But to really address in what circumstances choices should be offered, to whom and what type of choice, we need theoretical tools to help us understand and be attentive to the wider implications and the papers in this Issue help us to do that.Ethics statementsPatient consent for publicationNot applicable.Ethics approvalThis study does not involve human participants.IntroductionLarge-scale, international data sharing opens the door to the study of so-called ‘Big Data’, which holds great promise for improving patient-centred care. Big Data health research is envisioned to take precision medicine to the next level through increased understanding of disease aetiology and phenotypes, treatment effects, disease management and healthcare expenditure.1 However, lack of public trust is proven to be detrimental to the goals of data sharing.2 The case of care.data in the UK offers a blatant example of a data sharing initiative gone awry.

Criticism predominantly focused on limited public awareness and lack of clarity on the goals of the programme and ways to opt out.3 Citizens are becoming increasingly aware and critical of data privacy issues, and this warrants renewed investments to maintain public trust in data-intensive health research. Here, we use the term data-intensive health research to refer to a practice of grand-scale capture, (re)use and/or linkage of a wide variety of health-related data on individuals.Within the European Union (EU), the recently adopted General Data Protection Regulation (GDPR) (EU 2016/679) addresses some of the concerns the public may have with respect to privacy and data protection. One of the primary goals of the GDPR is to give individuals control over their personal data, most notably through consent.4 Other lawful grounds for the processing of personal data are listed, but it is unclear how these would exactly apply to scientific research. Legal norms remain open to interpretation and thus offer limited guidance to researchers.5 6 In Recital 33, the GDPR actually mentions that additional ethical standards are necessary for the processing of personal data for scientific research. This indicates a recognised need for entities undertaking activities likely to incite public unease to go beyond compliance with legal requirements.7 Complementary ethical governance then becomes a prerequisite for securing public trust in data-intensive health research.A concept that could be of use in developing ethical governance is that of a ‘social license to operate’.7 The social license captures the notion of a mandate granted by society to certain occupational groups to determine for themselves what constitutes proper conduct, under the condition that such conduct is in line with society’s expectations.

The term ‘social license’ was first used in the 1950s by American sociologist Everett Hughes to address relations between professional occupations and society.8 The concept has been used since to frame, for example, corporate social responsibility in the mining industry,9 governance of medical research in general8 and of data-intensive health research more specifically.7 10 As such, adequate ethical governance then becomes a precondition for obtaining a social license for data sharing activities.Key to an informed understanding of the social license is identifying the expectations society may hold with regard to sharing of and access to health data. Here, relevant societal actors are the subjects of Big Data health research, constituting both patients and the general public. Identification of patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework. We know of the existence of research papers that have captured these views using quantitative or qualitative methods or a combination of both. So far, systematic reviews of the literature have limited their scope to citizens of specific countries,11 12 qualitative studies only13 or the sharing of genomic data.14 Therefore, we performed an up-to-date narrative review of both quantitative and qualitative studies to explore predominant patient and public views and attitudes towards data sharing for health research.MethodsWe searched the literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar in April 2019 for publications addressing patients’ and public views and attitudes towards the use of health data for research purposes.

Synonyms of the following terms (connected by ‘AND’) were used to search titles and/or abstracts of indexed references. Patient or public. Views. Data sharing. Research (See box 1 and online supplementary appendix 1).

To merit inclusion, an article had to report results from an original research study (qualitative, quantitative or mixed methods) on attitudes of individuals regarding use of data for health research. We restricted eligibility to records published in English and studies performed between 2009 and 2019. We chose 2009 as a lower limit because we assume that patients’ and public perspectives might have changed substantially with increasing awareness and use of digital (health) technologies. Systematic reviews and meta-analyses synthesising the empirical literature on this topic also qualified for review. Reports from stakeholder meet-ups and workshops were eligible as long as they included patients or the public as participants.

Since we were only interested in empirical evidence, expert opinion and publications merely advocating for the inclusion of patients’ and public views in Big Data health research were excluded. Studies that predominantly reported on views of other stakeholders—such as clinicians, researchers, policy makers or industry—were excluded. Articles reporting on conference proceedings, or views regarding (demographic) data collection in low or middle income countries or for public health and care/quality improvement were not considered relevant to this review. Despite our specific interest in data sharing within the European context, we broadened eligibility criteria to include studies performed in the USA, Canada, Australia and New Zealand. Additional articles were identified through consultation with experts and review of references in the manuscript identified through the literature database searches.

Views and attitudes of patients and the public were identified from selected references and reviewed by means of thematic content analysis.Supplemental materialBox 1 Key search terms(patient* OR public OR citizen*)AND(attitude* OR view* OR perspective* OR opinion* OR interview* OR qualitative* OR questionnaire* OR survey*)AND(“data sharing” OR “data access” OR “data transfer”)ANDResearchResultsStudy characteristicsSearches in PubMed (MEDLINE), Embase, Scopus and Google Scholar resulted in a total of 1153 non-unique records (see online supplementary appendix 1). We identified 27 papers for review, including 12 survey or questionnaire studies (quantitative), 8 interview or focus group studies (qualitative), 1 mixed methods study and 6 systematic reviews (see table 1). Most records were excluded because they were not relevant to our research question or because they did not report on findings from original (empirical) research studies. Ten studies reported on views of patients, 11 on views of the public/citizens and 6 studies combined views of patients, research participants and the public.View this table:Table 1 Study characteristicsWillingness to share data for health researchReviewed papers suggest widespread support for the sharing of data for health research.Four systematic reviews synthesising the views of patients and the public report that willingness for data to be linked and shared for research purposes is high11–14 and that people are generally open to and understand the benefits of data sharing.15Outpatients from a German university hospital who participated in a questionnaire study (n=503) expressed a strong willingness (93%) to give broad consent for secondary use of data,16 and 93% of a sample of UK citizens with Parkinson’s disease (n=306) were willing to share their data.17 Wide support for sharing of data internationally18 19 and in multicentre studies20 was reported among patient participants. Goodman et al found that most participants in a sample of US patients with cancer (n=228) were willing to have their data made available for ‘as many research studies as possible’.21 Regarding the use of anonymised healthcare data for research purposes, a qualitative study found UK rheumatology patients and patient representatives in support of data sharing (n=40).22Public respondents in survey studies recognised the benefits of storing electronic health information,23 and 78.8% (n=151) of surveyed Canadians felt positive about the use of routinely collected data for health research.24 The majority (55%) of a sample of older Swiss citizens (n=40) were in favour of placing genetic data at disposal for research.25 Focus group discussions convened in the UK showed that just over 50% of the members of the Citizens Council of The National Institute for Health and Care Excellence (NICE) said they would have no concerns about NICE using anonymised data derived from personal care records to evaluate treatments,26 and all participants in one qualitative study were keen to contribute to the National Healthcare Service (NHS)-related research.27Motivations to share dataPatients and public participants expressed similar reasons and motivations for their willingness to share data for health research, including contributing to advancements in healthcare, returning incurred benefits and the hope of future personal health benefits (tables 2–4).View this table:Table 2 Patients’ views and attitudes towards the sharing of health data for researchView this table:Table 3 Public views and attitudes towards the sharing of health data for researchView this table:Table 4 Patients’ and public views and attitudes towards the sharing of health data for researchIn the two systematic reviews that addressed this topic, sharing data for ‘the common good’ or ‘the greater good’ was identified as one of the most prevalent motivations.12 14For patients specifically, to help future patients or people with similar health problems was an important reason.14 16 One survey study conducted among German outpatients found that 72% listed returning their own benefits incurred from research as a driver for sharing clinical data.16 Patients with rare disease were also motivated by ‘great hope and trust’ in the development of international databases for health research.19 Among patients, support of research in general,16 the value attached to answering ‘important’ research questions,20 and a desire to contribute to advancements in medicine14 were prevalent reasons in favour of data sharing.

Ultimately, the belief that data sharing could lead to improvements in health outcome and care was reported.20Only one original study research paper addressed public motivations. This study found that older citizens mentioned auistic reasons and the greater good in a series of interviews as reasons to share genetic data for research.25 In these interviews, citizens expressed no expectations of an immediate impact or beneficial return but ultimately wanted to help the next generation.Perceived benefits of data sharingPatients and the public perceive that data sharing could lead to better patient care through improved diagnosis and treatment options and more efficient use of resources. Patients seem to also value the potential of (direct) personal health benefits.Two systematic reviews reported on perceived benefits of data sharing for health research purposes. Howe et al mentioned perceived benefits to research participants or the immediate community, benefits to the public and benefits to research and science.15 Shabani et al also listed accelerating research advancement and maximising the value of resources as perceived benefits.14Surveyed patients perceived that data sharing could help their doctor ‘make better decisions’ about their health (94%, n=3516)28 or result in an increased chance of receiving personalised health information (n=228).21In the original studies reviewed, advantages and potential benefits of data sharing were generally recognised by public and patient participants.22 29 Data sharing was believed to enable the study of long-term treatment effects and rare events, as well as the study of large numbers of people,24 to improve diagnosis25 and treatment quality,20 23 as well as to stimulate innovation30 and identify new treatment options.25 A cross-sectional online survey among patient and citizen groups in Italy (n=280) also identified the perception that data sharing could reduce waste in research.30Perceived risks of data sharingThe most significant risks of data sharing were perceived to results from breaches of confidentiality, commercial use and potential abuse of the data.Systematic reviews report on patients’ and public concerns about confidentiality in general,13 15 sometimes linked to the risk of reidentification,14 concerns about a party's competence in keeping data secure,12 and concerns that personal information could be mined from genomic data.14 A systematic review by Stockdale et al identified concerns among the public (UK and Ireland) about the motivation a party might have to use the data.14Patients in a UK qualitative study (n=40) perceived ‘detrimental’ consequences of data ‘falling into the wrong hands’, such as insurance companies.22 Respondents from the online patient community PatientsLikeMe were fearful of health data being ‘stolen by hackers’ (87%, n=3516).28Original research studies flagged data security and privacy as major public concerns.16 18 20 25 26 29–32 More specifically, many studies found that participants worried about who would have access to the data and about risk of misuses or abuses.13 15 18 25 27 33 A large pan-European survey among respondents from 27 EU member states revealed public concerns about different levels of access by third parties (48.9%–60.6%, n=20 882).23 Overall, reviewed papers suggest that patients and the public are concerned about the use of their data for commercial purposes.14 27 For example, the NICE Citizens Council expressed concerns about the potential for data to be sold to other organisations and used for profit and for purposes other than research.26 The Citizens Council also highlighted the need for transparency about how data are used and how it might be used in the future and for ensuring the research is conducted according to good scientific practice and that data are used to benefit society. Concerns about control and ownership of data were identified13 33 and about re-use of data for purposes that participants do not agree on.30 Fear of discrimination, stigmatisation, exploitation or other repercussions as a consequence of data being shared was widely cited by individuals.14 15 18Barriers to share dataStudies showed that patients and the public rarely mention barriers to data sharing in absolute terms.

Rather, acceptance seemed to decrease if data sharing was financially motivated, and if people did not know how and with whom their data would be shared.First, individuals often opposed data sharing if it was motivated by financial gain or profit20 or if the data were shared with commercial/private companies.14 15 In one large pan-European survey (n=20 882), respondents were found to be strongly averse to health insurance companies and private sector pharmaceutical companies viewing their data.23 Second, lack of understanding and awareness around the use of data was viewed as a barrier to data sharing.15 22 Third, lack of transparency and controllability in releasing data were mentioned as factors compromising public trust in data sharing activities.14 22Factors affecting willingness to share dataA wide range of factors were identified from the literature that impacted individuals’ willingness to share data for health research, including geographical factors, age, individual-specific and research-specific characteristics.Geographical factorsMcCormack et al found that European patients’ expressions of trust and attitudes to risk were often affected by the regulatory and cultural practices in their home countries, as well as by the nature of the (rare) disease the patient participant had.18 Shah et al conducted a survey among patients in four Northern European countries (n=855) and found a significant association between country and attitudes towards sharing of deidentified data.34 Interestingly, Dutch respondents were less likely to support sharing of their deidentified data compared with UK citizens.AgeAmong a sample of surveyed patients with Parkinson’s disease (UK), a significant association was found between higher age and increased support for data sharing.17 According to a study based on semistructured interviews with older Swiss citizens, generational differences impacted willingness to share.25 With respect to public attitudes towards data sharing, findings of one systematic review suggest that males and older people are more likely to consent to sharing their medical data.27 A systematic review by Shabani et al suggests that patient and public participants with higher mean age are substantially less worried about privacy and confidentiality than other groups.14Individual-specific characteristicsA systematic review into patients’ and public perspectives on data sharing in the USA suggests that individuals from under-represented minorities are less willing to share data.11 A large multisite survey (n=13 000) among the US public found that willingness to share was associated with self-identified white race, higher educational attainment and lower religiosity.31 In another systematic review, race, gender, age, marital status and/or educational level all seemed to influence how people perceived sensitivity of genomic data and the sharing thereof.14 However, a UK study among patients with Parkinson’s disease found no clear relationship between data sharing and the number of years diagnosed, sex, medication class or health confidence.17Factors that clearly positively affected attitudes towards data sharing were perceptions of the (public) benefits and value of the research,13 20 fewer concerns and fewer information needs,31 and higher trust in and reputation of individuals or organisations conducting and/or overseeing data sharing.12–14 35 Conversely, willingness decreased with higher privacy and confidentiality concerns11 and higher distrust of the government as an oversight body for (genetic) research data.35Research-specific characteristicsPrivacy measures increased people’s willingness to share their data for health research, such as removal of social security numbers (90%, n=3516) and insurance ID (82%, n=3516), the sharing of only summary-level or aggregate data20 and deposition of data in a restricted access online database.29 Expressions of having control over what data are shared and with whom positively affected attitudes towards data sharing.34 In one study, being asked for consent for each study made participants (81%) feel ‘respected and involved’, and 74% agreed that they would feel that they ‘had control’.14 With respect to data sharing without prospective consent, participants became more accepting after being given information about the research processes and selection bias.27 Less support was observed for data sharing due to financial incentives25 and, more specifically, if data would be shared with private companies, such as insurance or pharmaceutical companies.11 25Conditions for sharingWidespread willingness to share data for health research very rarely led to participants’ unconditional support. Studies showed agreement on the following conditions for responsible data sharing. Value, privacy, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.ValueOne systematic review found that participants found it important that the research as a result of data sharing should be in the public’s interest and should reflect participants’ values.15 The NICE Citizens Council advocated for appropriate systems and good working practices to ensure a consistent approach to research planning, data capture and analysis.26Privacy, risks and data securityThe need to protect individuals’ privacy was considered paramount11 14 21 34 and participants often viewed deidentification of personal data as a top privacy measure.11 24 30 36 One survey among US patients with cancer found that only 20% (n=228) of participants found linkage of individuals with their deidentified data acceptable for return of individual health results and to support further research.21 Secured access to databases was considered an important measure to ensure data security in data sharing activities.30 34 A systematic review of participants’ attitudes towards data sharing showed that people established risk minimisation as another condition for data sharing.15 Findings by Mazor et al suggest that patients only support studies that offer value and minimise security risks.20Transparency and controlConditions regarding transparency were information about how data will be shared and with whom,14 35 the type of research that is to be performed, by whom the research will be performed,16 information on data sharing and monitoring policies and database governance,35 conditions framing access to data and data access agreements,24 28 30 and any partnerships with the pharmaceutical industry.19 More generally, participants expressed the desire to be involved in the data sharing process,35 to be notified when their data are (re)used and to be informed of the results of studies using their data.15 Spencer et al identified use of an electronic interface as a highly valued means to enable greater control over consent choices.22 When asked about the use of personal data for health research by the NHS, UK citizens were typically willing to accept models of consent other than the ones they would prefer.37 Acceptance of consent models with lower levels of individual control was found to be dependent on a number of factors, including adequate transparency, control over detrimental use and commercialisation, and the ability to object, particularly to any processing considered to be inappropriate or particularly sensitive.37Information and trustOne systematic review identified trust in the ability of the original institution to carry out the oversight tasks as a major condition for responsible data sharing.14 Appropriate education and information about data sharing was thought to include public campaigns to inform stakeholders about Big Data32 and information communicated at open days of research institutions (such as NICE) to ensure people understand what their data are being used for and to reassure them that personal data will not be passed on or sold to other organisations.26 The informed consent process for study participation was believed to include information about the fact that individuals’ data could potentially be shared,15 30 the objectives of data sharing and (biobank) research, the study’s data sharing plans,29 governance structure, logistics and accountability.33Responsibility and accountabilityParticipants often placed the responsibility for data sharing practices on the shoulders of researchers. Secondary use of data collected earlier for scientific research was viewed to require a data access committee that involves a researcher from the original research project, a clinician, patient representative and a participant in the original study.36 Researchers of the original study were required to monitor data used by other researchers.36 In terms of accountability, patient and public groups in Italy (n=280) placed high value on sanctions for misuse of data.30 Information on penalties or other consequences of a breach of protection or misuse was considered important by many.31 35DiscussionIn this study, we narratively reviewed 27 papers on patients’ and public views on and attitudes towards the use of health data for scientific research. Studies reported a widespread—though conditional—support for the linkage and sharing of data for health research.

The only outlier seems to be the finding that just over half (n=25) of the NICE Citizens Council answered ‘no’ to the question whether they had any concerns if NICE used anonymised data to fill in the gaps if NICE was not getting enough evidence in ‘the usual ways’.26 However, we hasten to point out that the question about willingness to share is different from the question whether people have concerns or not. In addition, after a 2-day discussion meeting Council members were perhaps more sensitised to the potential concerns regarding data sharing. Therefore, we suggest that the way and context within which questions are phrased may influence the answers people give.Overall, people expressed similar motivations to share their data, perceived similar benefits (despite some variation between patients and citizens), yet at the same time displayed a range of concerns, predominantly relating to confidentiality and data security, awareness about access and control, and potential harms resulting from these risks. Both patient and public participants conveyed that certain factors would increase or reduce their willingness to have their data shared. For example, the presence of privacy-protecting measures (eg, data deidentification and the use of secured databases) seemed to increase willingness to share, as well as transparency and information about data sharing processes and responsibilities.

The identified views and attitudes appeared to come together in the conditions stipulated by participants. Value, privacy and confidentiality, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.In our Introduction, we mentioned that identifying patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework. In other words, what work should our governance framework be doing in order to obtain a social license?. This review urges researchers and institutions to address people’s diverse concerns and to make an effort to meet the conditions identified. Without these conditions, institutions lack trustworthiness, which is vital for the proceedings of medicine and biomedical science.

As such, a social license is not a ‘nice to have’ but a ‘need to have’. Our results also confirm that patients and the public indeed care about more than legal compliance alone, and wish to be engaged through information, transparency and control. This work supports the findings of a recent systematic review into ethical principles of data sharing as specified in various international ethical guidelines and literature.38 What this body of research implies is considerable diversity of values and beliefs both between and within countries.The goal of this narrative review was to identify the most internationally dominant, aggregated patient and public views about the broad topic of data sharing for health research. We deliberately opted for the methodology of a narrative review rather than a systematic review. Most narrative reviews deal with a broad range of issues to a given topic rather than addressing a particular topic in depth.39 This means narrative reviews may be most useful for obtaining a broad perspective on a topic, and that they often are less useful in generating quantitative answers to specific clinical questions.

However, because narrative reviews do not require specification of the search and selection strategy and the way of critically appraising literature can be variable, the connection between evidence generated by narrative reviews and (clinical) recommendations is less rigorous and risk of bias exists. This is something to take into account in this study. A risk of bias assessment was not possible due to the heterogeneity of the findings. We acknowledge that our methodological choices may have affected the discriminative power or granularity of our findings. For example, there is a difference between sharing of routinely collected health data versus secondary use of health data collected for research purposes.

And we can only make loose assumptions about potential differences between patient and public views.In addition, we should mention that this work is centred around studies conducted in Western countries as the whole Big Data space and literature is dominated by Western countries, higher socioeconomic status and Caucasians. However, most of the disease burden globally and within countries is most probably not represented in the ‘Big Data’ and so we have to stress the lack of generalisability to large parts of the world.Nevertheless, we believe our findings point towards essential elements of a governance framework for data sharing for health research purposes. If we are to conclude that the identified conditions ought to act as the pillars of a governance framework, the next step is to identify how these conditions could be practically operationalised. For example, if people value information, transparency and control, what type of consent is most likely to valorise these conditions?. And what policy for returning research results would be desirable?.

Once we know what to value, we can start thinking about the ways to acknowledge that value. A new challenge arising here, however, is what to do when people hold different or even conflicting values or preferences. Discrete choice experiments could help to test people’s preferences regarding specific topics, such as preferred modes of informed consent. Apart from empirical work, conceptual analysis is needed to clarify how public trust, trustworthiness of institutions and accountability are interconnected.ConclusionThis narrative review suggests widespread—though conditional—support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of health research, they report a number of significant concerns and related conditions.

We believe identified conditions (eg, social value, data security, transparency and accountability) ought to be operationalised in a value-based governance framework that incorporates the diverse patient and public values, needs and interests, and which reflects the way these same conditions are met, to strengthen the social license for Big Data health research.Ethics statementsPatient consent for publicationNot required.AcknowledgmentsWe thank Susanne Løgstrup (European Heart Network) and Evert-Ben van Veen (Medlaw) for their valuable feedback during various stages in drafting the manuscript..

Viagra 100

Patients Figure viagra 100 http://www.em-prunelliers-bischheim.site.ac-strasbourg.fr/lequipe/les-atsems/ 1. Figure 1. Enrollment and viagra 100 Randomization.

Of the 1114 patients who were assessed for eligibility, 1062 underwent randomization. 541 were viagra 100 assigned to the remdesivir group and 521 to the placebo group (intention-to-treat population) (Figure 1). 159 (15.0%) were categorized as having mild-to-moderate disease, and 903 (85.0%) were in the severe disease stratum.

Of those viagra 100 assigned to receive remdesivir, 531 patients (98.2%) received the treatment as assigned. Fifty-two patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death and 10 withdrew consent. Of those viagra 100 assigned to receive placebo, 517 patients (99.2%) received placebo as assigned.

Seventy patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death and 14 withdrew consent. A total of 517 patients in the remdesivir group and 508 in the placebo group completed the trial through day 29, recovered, or died. Fourteen patients who received remdesivir and 9 who received viagra 100 placebo terminated their participation in the trial before day 29.

A total of 54 of the patients who were in the mild-to-moderate stratum at randomization were subsequently determined to meet the criteria for severe disease, resulting in 105 patients in the mild-to-moderate disease stratum and 957 in the severe stratum. The as-treated population included 1048 patients who received the assigned treatment (532 in the remdesivir group, including one patient who had been randomly assigned to placebo and received remdesivir, viagra 100 and 516 in the placebo group). Table 1.

Table 1 viagra 100. Demographic and Clinical Characteristics of the Patients at Baseline. The mean age of the patients was viagra 100 58.9 years, and 64.4% were male (Table 1).

On the basis of the evolving epidemiology of erectile dysfunction treatment during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1 in the Supplementary Appendix). Overall, 53.3% of the patients were White, 21.3% were Black, 12.7% were Asian, and 12.7% were designated as other or not reported. 250 (23.5%) were Hispanic or Latino viagra 100.

Most patients had either one (25.9%) or two or more (54.5%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (50.2%), obesity (44.8%), and type 2 diabetes mellitus (30.3%). The median number of days between symptom onset and randomization was 9 (interquartile range, 6 to viagra 100 12) (Table S2). A total of 957 patients (90.1%) had severe disease at enrollment.

285 patients (26.8%) met category 7 criteria viagra 100 on the ordinal scale, 193 (18.2%) category 6, 435 (41.0%) category 5, and 138 (13.0%) category 4. Eleven patients (1.0%) had missing ordinal scale data at enrollment. All these patients discontinued the study before viagra 100 treatment.

During the study, 373 patients (35.6% of the 1048 patients in the as-treated population) received hydroxychloroquine and 241 (23.0%) received a glucocorticoid (Table S3). Primary Outcome viagra 100 Figure 2. Figure 2.

Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates are shown in the overall population (Panel A), in patients with a baseline viagra 100 score of 4 on the ordinal scale (not receiving oxygen. Panel B), in those with a baseline score of 5 (receiving oxygen.

Panel C), in those with a baseline score of 6 (receiving viagra 100 high-flow oxygen or noninvasive mechanical ventilation. Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or extracorporeal membrane oxygenation [ECMO]. Panel E).Table 2 viagra 100.

Table 2. Outcomes Overall and According to Score on the viagra 100 Ordinal Scale in the Intention-to-Treat Population. Figure 3.

Figure 3. Time to Recovery According to Subgroup viagra 100. The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects.

Race and ethnic group were reported by the patients.Patients in the remdesivir group had a shorter time to recovery than patients in the placebo group (median, viagra 100 10 days, as compared with 15 days. Rate ratio for recovery, 1.29. 95% confidence interval viagra 100 [CI], 1.12 to 1.49.

P<0.001) (Figure 2 and Table 2). In the severe disease stratum (957 patients) the median time to recovery was 11 days, as compared with 18 days (rate ratio for recovery, viagra 100 1.31. 95% CI, 1.12 to 1.52) (Table S4).

The rate ratio for recovery was viagra 100 largest among patients with a baseline ordinal score of 5 (rate ratio for recovery, 1.45. 95% CI, 1.18 to 1.79). Among patients with a baseline score of 4 and those with a baseline score of 6, the rate ratio estimates for recovery were 1.29 (95% CI, 0.91 to 1.83) and 1.09 (95% CI, 0.76 to 1.57), respectively.

For those receiving mechanical ventilation or ECMO at viagra 100 enrollment (baseline ordinal score of 7), the rate ratio for recovery was 0.98 (95% CI, 0.70 to 1.36). Information on interactions of treatment with baseline ordinal score as a continuous variable is provided in Table S11. An analysis adjusting for baseline ordinal score as a covariate was conducted to evaluate the overall effect (of the percentage of patients in each ordinal score category at viagra 100 baseline) on the primary outcome.

This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.26. 95% CI, 1.09 viagra 100 to 1.46). Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.37 (95% CI, 1.14 to 1.64), whereas patients who underwent randomization more than 10 days after the onset of symptoms had a rate ratio for recovery of 1.20 (95% CI, 0.94 to 1.52) (Figure 3).

The benefit of viagra 100 remdesivir was larger when given earlier in the illness, though the benefit persisted in most analyses of duration of symptoms (Table S6). Sensitivity analyses in which data were censored at earliest reported use of glucocorticoids or hydroxychloroquine still showed efficacy of remdesivir (9.0 days to recovery with remdesivir vs. 14.0 days to recovery with placebo.

Rate ratio, 1.28 viagra 100. 95% CI, 1.09 to 1.50, and 10.0 vs. 16.0 days to viagra 100 recovery.

Rate ratio, 1.32. 95% CI, 1.11 viagra 100 to 1.58, respectively) (Table S8). Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as determined by a proportional odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.5.

95% CI, 1.2 to 1.9, adjusted for disease viagra 100 severity) (Table 2 and Fig. S7). Mortality Kaplan–Meier estimates of mortality by day 15 were 6.7% in the remdesivir group and 11.9% in the placebo group (hazard ratio, 0.55.

95% CI, 0.36 viagra 100 to 0.83). The estimates by day 29 were 11.4% and 15.2% in two groups, respectively (hazard ratio, 0.73. 95% CI, viagra 100 0.52 to 1.03).

The between-group differences in mortality varied considerably according to baseline severity (Table 2), with the largest difference seen among patients with a baseline ordinal score of 5 (hazard ratio, 0.30. 95% CI, 0.14 to 0.64) viagra 100. Information on interactions of treatment with baseline ordinal score with respect to mortality is provided in Table S11.

Additional Secondary viagra 100 Outcomes Table 3. Table 3. Additional Secondary viagra 100 Outcomes.

Patients in the remdesivir group had a shorter time to improvement of one or of two categories on the ordinal scale from baseline than patients in the placebo group (one-category improvement. Median, 7 vs. 9 days viagra 100.

Rate ratio for recovery, 1.23. 95% CI, 1.08 viagra 100 to 1.41. Two-category improvement.

Median, 11 viagra 100 vs. 14 days. Rate ratio, viagra 100 1.29.

95% CI, 1.12 to 1.48) (Table 3). Patients in the remdesivir group had a shorter time to discharge or to a National Early Warning Score of 2 or lower than those in the placebo group (median, 8 days vs. 12 days viagra 100.

Hazard ratio, 1.27. 95% CI, 1.10 to 1.46) viagra 100. The initial length of hospital stay was shorter in the remdesivir group than in the placebo group (median, 12 days vs.

17 days) viagra 100. 5% of patients in the remdesivir group were readmitted to the hospital, as compared with 3% in the placebo group. Among the 913 patients receiving oxygen at enrollment, those in the remdesivir group continued to viagra 100 receive oxygen for fewer days than patients in the placebo group (median, 13 days vs.

21 days), and the incidence of new oxygen use among patients who were not receiving oxygen at enrollment was lower in the remdesivir group than in the placebo group (incidence, 36% [95% CI, 26 to 47] vs. 44% [95% CI, 33 to 57]) viagra 100. For the 193 patients receiving noninvasive ventilation or high-flow oxygen at enrollment, the median duration of use of these interventions was 6 days in both the remdesivir and placebo groups.

Among the 573 patients who were not receiving noninvasive ventilation, high-flow oxygen, invasive ventilation, or ECMO at baseline, the incidence of new noninvasive ventilation or high-flow oxygen use was lower in the remdesivir group than in the placebo group (17% [95% CI, 13 to 22] vs. 24% [95% CI, viagra 100 19 to 30]). Among the 285 patients who were receiving mechanical ventilation or ECMO at enrollment, patients in the remdesivir group received these interventions for fewer subsequent days than those in the placebo group (median, 17 days vs.

20 days), and the incidence of new mechanical ventilation or ECMO use among the 766 patients who were not receiving these interventions at enrollment was lower in the remdesivir group than in the placebo group (13% [95% CI, 10 to 17] vs viagra 100. 23% [95% CI, 19 to 27]) (Table 3). Safety Outcomes In the as-treated population, serious adverse events occurred in viagra 100 131 of 532 patients (24.6%) in the remdesivir group and in 163 of 516 patients (31.6%) in the placebo group (Table S17).

There were 47 serious respiratory failure adverse events in the remdesivir group (8.8% of patients), including acute respiratory failure and the need for endotracheal intubation, and 80 in the placebo group (15.5% of patients) (Table S19). No deaths were considered by the investigators to be related to treatment viagra 100 assignment. Grade 3 or 4 adverse events occurred on or before day 29 in 273 patients (51.3%) in the remdesivir group and in 295 (57.2%) in the placebo group (Table S18).

41 events were judged by the investigators to be related to remdesivir and 47 events to placebo (Table S17). The most common viagra 100 nonserious adverse events occurring in at least 5% of all patients included decreased glomerular filtration rate, decreased hemoglobin level, decreased lymphocyte count, respiratory failure, anemia, pyrexia, hyperglycemia, increased blood creatinine level, and increased blood glucose level (Table S20). The incidence of these adverse events was generally similar in the remdesivir and placebo groups.

Crossover After the data and safety monitoring board recommended that the preliminary primary analysis report be viagra 100 provided to the sponsor, data on a total of 51 patients (4.8% of the total study enrollment) — 16 (3.0%) in the remdesivir group and 35 (6.7%) in the placebo group — were unblinded. 26 (74.3%) of those in the placebo group whose data were unblinded were given remdesivir. Sensitivity analyses evaluating the unblinding (patients whose treatment assignments were unblinded had their data censored at the time of unblinding) and crossover (patients in the placebo group treated with remdesivir had their data censored at the initiation of remdesivir treatment) produced results similar to those of the primary analysis (Table S9).Study Design and Participants To reduce the risk of introducing erectile dysfunction into basic training at Marine Corps Recruit Depot, Parris Island, in South Carolina, the Marine Corps established viagra 100 a 14-day supervised quarantine period at a college campus used exclusively for this purpose.

Potential recruits were instructed to quarantine at home for 2 weeks immediately before they traveled to campus. At the end viagra 100 of the second, supervised quarantine on campus, all recruits were required to have a negative qPCR result before they could enter Parris Island. Recruits were asked to participate in the erectile dysfunction treatment Health Action Response for Marines (CHARM) study, which included weekly qPCR testing and blood sampling for IgG antibody assessment.

After potential recruits had completed the 14-day home quarantine, they presented to a local Military Entrance Processing Station, where a medical history was taken and a physical examination was performed. If potential recruits were deemed to be physically and mentally fit for http://www.col-twinger-strasbourg.site.ac-strasbourg.fr/aides/lati/ enlistment, they were instructed to wear masks at all times and maintain social distancing of at least 6 feet during travel to the viagra 100 quarantine campus. Classes of 350 to 450 recruits arrived on campus nearly weekly.

New classes were divided into platoons of 50 to 60 recruits, and roommates were assigned independently of participation in the viagra 100 CHARM study. Overlapping classes were housed in different dormitories and had different dining times and training schedules. During the supervised quarantine, public health measures were enforced to suppress erectile dysfunction transmission (Table S1 in viagra 100 the Supplementary Appendix, available with the full text of this article at NEJM.org).

All recruits wore double-layered cloth masks at all times indoors and outdoors, except when sleeping or eating. Practiced social distancing viagra 100 of at least 6 feet. Were not allowed to leave campus.

Did not have access to personal electronics and viagra 100 other items that might contribute to surface transmission. And routinely washed their hands. They slept in double-occupancy rooms with sinks, ate in shared dining facilities, and used shared bathrooms.

All recruits cleaned their rooms daily, sanitized bathrooms after each use with bleach wipes, and ate preplated meals in a dining hall that was cleaned with bleach after each viagra 100 platoon had eaten. Most instruction and exercises were conducted outdoors. All movement of recruits was supervised, and unidirectional flow was implemented, with designated viagra 100 building entry and exit points to minimize contact among persons.

All recruits, regardless of participation in the study, underwent daily temperature and symptom screening. Six instructors who were assigned to each platoon worked in 8-hour shifts and enforced the quarantine measures viagra 100. If recruits reported any signs or symptoms consistent with erectile dysfunction treatment, they reported to sick call, underwent rapid qPCR testing for erectile dysfunction, and were placed in isolation pending the results of testing.

Instructors were also restricted to viagra 100 campus, were required to wear masks, were provided with preplated meals, and underwent daily temperature checks and symptom screening. Instructors who were assigned to a platoon in which a positive case was diagnosed underwent rapid qPCR testing for erectile dysfunction, and, if the result was positive, the instructor was removed from duty. Recruits and instructors were prohibited from interacting with campus support staff, such as janitorial and food-service personnel.

After each class completed quarantine, a deep bleach cleaning of surfaces was performed in the bathrooms, showers, bedrooms, and hallways in the dormitories, and the dormitory remained viagra 100 unoccupied for at least 72 hours before reoccupancy. Within 2 days after arrival at the campus, after recruits had received assignments to platoons and roommates, they were offered the opportunity to participate in the longitudinal CHARM study. Recruits were eligible if they were viagra 100 18 years of age or older and if they would be available for follow-up.

The study was approved by the institutional review board of the Naval Medical Research Center and complied with all applicable federal regulations governing the protection of human subjects. All participants viagra 100 provided written informed consent. Procedures At the time of enrollment, participants answered a questionnaire regarding demographic characteristics, risk factors for erectile dysfunction , symptoms within the previous 14 days, and a brief medical history.

Blood samples viagra 100 and mid-turbinate nares swab specimens were obtained for qPCR testing to detect erectile dysfunction. Demographic information included sex, age, ethnic group, race, place of birth, and U.S. State or country of residence viagra 100.

Information regarding risk factors included whether participants had used masks, whether they had adhered to self-quarantine before arrival, their recent travel history, their known exposure to someone with erectile dysfunction treatment, whether they had flulike symptoms or other respiratory illness, and whether they had any of 14 specific symptoms characteristic of erectile dysfunction treatment or any other symptoms associated with an unspecified condition within the previous 14 days. Study participants were followed up on days 7 and 14, at which time they reported any symptoms that had occurred within the past 7 days. Nares swab specimens for repeat qPCR assays were also viagra 100 obtained.

Participants who had positive qPCR results were placed in isolation and were approached for participation in a related but separate study of infected recruits, which involved more frequent testing during isolation. All recruits who did not participate in the current study were tested for erectile dysfunction only at the end of the 2-week quarantine, viagra 100 unless clinically indicated (in accordance with the public health procedures of the Marine Corps). Serum specimens obtained at enrollment were tested for erectile dysfunction–specific IgG antibodies with the use of the methods described below and in the Supplementary Appendix.

Participants who tested positive on the day of enrollment (day 0) viagra 100 or on day 7 or day 14 were separated from their roommates and were placed in isolation. Otherwise, participants and nonparticipants were not treated differently. They followed the same viagra 100 safety protocols, were assigned to rooms and platoons regardless of participation in the study, and received the same formal instruction.

Laboratory Methods The qPCR testing of mid-turbinate nares swab specimens for erectile dysfunction was performed within 48 hours after collection by Lab24 (Boca Raton, FL) with the use of the TaqPath erectile dysfunction treatment Combo Kit (Thermo Fisher Scientific), which is authorized by the Food and Drug Administration. Specimens obtained from nonparticipants were tested by the Naval Medical Research Center (Silver Spring, MD). Specimens were stored in viral transport medium at 4°C viagra 100.

The presence of IgG antibodies specific to the erectile dysfunction receptor-binding (spike) domain in serum specimens was evaluated with the use of an enzyme-linked immunosorbent assay, as previously described,10 with some modifications. At least two positive controls, viagra 100 eight negative controls (serum specimens obtained before July 2019), and four blanks (no serum) were included in every plate. Serum specimens were first screened at a 1:50 dilution, followed by full dilution series if the specimens were initially found to be positive.

Whole-Genome Sequencing and Assembly erectile dysfunction sequencing was performed with the use of two sequencing protocols (an Illumina sequencing protocol and an Ion Torrent sequencing protocol) viagra 100 to increase the likelihood of obtaining complete genome sequences. A custom reference-based analysis pipeline (https://github.com/mjsull/erectile dysfunction treatment_pipe) was used to assemble erectile dysfunction genomes with the use of data from Illumina, Ion Torrent, or both.11 Phylogenetic Analysis erectile dysfunction genomes obtained from patients worldwide and associated metadata were downloaded from the Global Initiative on Sharing All Influenza Data EpiCoV database12 on August 11, 2020 (79,840 sequences), and a subset of sequences was selected from this database with the use of the default subsampling scheme of Nextstrain software13 with the aim of maximizing representation of genomes obtained from patients in the United States. Phylogenetic analyses of the specimens obtained from participants were performed viagra 100 with the v1.0-292-ga9de690 Nextstrain build for erectile dysfunction genomes with the use of default parameters.

Transmission and outbreak events were identified on the basis of clustering of the erectile dysfunction genomes obtained from study participants within the Nextstrain phylogenetic tree, visualized with TreeTime.14 A comparative analysis of mutation profiles relative to the erectile dysfunction Wuhan reference genome was performed with the use of Nextclade software, version 0.3.6 (https://clades.nextstrain.org/). Data Analysis The denominator for calculating viagra 100 the percentage of recruits who had a first positive result for erectile dysfunction by qPCR assay on each day of testing excluded recruits who had previously tested positive, had dropped out of the study, were administratively separated from the Marine Corps, or had missing data. The denominator for calculating the cumulative positivity rates included all recruits who had undergone testing at previous time points, including those who were no longer participating in the study.

Only descriptive numerical results and percentages are reported, with no formal statistical analysis.Trial Population Table 1. Table 1 viagra 100. Characteristics of the Participants in the mRNA-1273 Trial at Enrollment.

The 45 enrolled participants received their viagra 100 first vaccination between March 16 and April 14, 2020 (Fig. S1). Three participants did not receive the second vaccination, including one in the 25-μg group who had urticaria on both legs, with onset 5 days after the first viagra 100 vaccination, and two (one in the 25-μg group and one in the 250-μg group) who missed the second vaccination window owing to isolation for suspected erectile dysfunction treatment while the test results, ultimately negative, were pending.

All continued to attend scheduled trial visits. The demographic viagra 100 characteristics of participants at enrollment are provided in Table 1. treatment Safety No serious adverse events were noted, and no prespecified trial halting rules were met.

As noted above, one participant in the 25-μg group was withdrawn because of an unsolicited adverse event, transient urticaria, judged to be related to the first vaccination. Figure 1 viagra 100. Figure 1.

Systemic and Local Adverse viagra 100 Events. The severity of solicited adverse events was graded as mild, moderate, or severe (see Table S1).After the first vaccination, solicited systemic adverse events were reported by 5 participants (33%) in the 25-μg group, 10 (67%) in the 100-μg group, and 8 (53%) in the 250-μg group. All were mild or moderate in severity (Figure 1 and Table viagra 100 S2).

Solicited systemic adverse events were more common after the second vaccination and occurred in 7 of 13 participants (54%) in the 25-μg group, all 15 in the 100-μg group, and all 14 in the 250-μg group, with 3 of those participants (21%) reporting one or more severe events. None of the participants had fever viagra 100 after the first vaccination. After the second vaccination, no participants in the 25-μg group, 6 (40%) in the 100-μg group, and 8 (57%) in the 250-μg group reported fever.

One of the events (maximum temperature, 39.6°C) in the 250-μg group was graded severe. (Additional details regarding adverse events for that participant are provided in the Supplementary Appendix.) Local adverse events, when present, were nearly all mild viagra 100 or moderate, and pain at the injection site was common. Across both vaccinations, solicited systemic and local adverse events that occurred in more than half the participants included fatigue, chills, headache, myalgia, and pain at the injection site.

Evaluation of safety clinical laboratory values of grade 2 or higher and unsolicited adverse events revealed no patterns of concern viagra 100 (Supplementary Appendix and Table S3). erectile dysfunction Binding Antibody Responses Table 2. Table 2 viagra 100.

Geometric Mean Humoral Immunogenicity Assay Responses to mRNA-1273 in Participants and in Convalescent Serum Specimens. Figure 2 viagra 100. Figure 2.

erectile dysfunction Antibody viagra 100 and Neutralization Responses. Shown are geometric mean reciprocal end-point enzyme-linked immunosorbent assay (ELISA) IgG titers to S-2P (Panel A) and receptor-binding domain (Panel B), PsVNA ID50 responses (Panel C), and live viagra PRNT80 responses (Panel D). In Panel A and Panel B, boxes and horizontal bars denote interquartile range (IQR) and median area under the curve (AUC), respectively.

Whisker endpoints are equal to the maximum and minimum values below or above the median ±1.5 times the IQR viagra 100. The convalescent serum panel includes specimens from 41 participants. Red dots indicate the 3 specimens that were viagra 100 also tested in the PRNT assay.

The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent serum panel. In Panel C, viagra 100 boxes and horizontal bars denote IQR and median ID50, respectively. Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR.

In the convalescent viagra 100 serum panel, red dots indicate the 3 specimens that were also tested in the PRNT assay. The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent panel. In Panel D, boxes and horizontal bars denote IQR and median PRNT80, respectively.

Whisker end points are equal to viagra 100 the maximum and minimum values below or above the median ±1.5 times the IQR. The three convalescent serum specimens were also tested in ELISA and PsVNA assays. Because of the time-intensive nature of the PRNT assay, for this preliminary report, PRNT results were available only for the 25-μg and 100-μg viagra 100 dose groups.Binding antibody IgG geometric mean titers (GMTs) to S-2P increased rapidly after the first vaccination, with seroconversion in all participants by day 15 (Table 2 and Figure 2A).

Dose-dependent responses to the first and second vaccinations were evident. Receptor-binding domain–specific viagra 100 antibody responses were similar in pattern and magnitude (Figure 2B). For both assays, the median magnitude of antibody responses after the first vaccination in the 100-μg and 250-μg dose groups was similar to the median magnitude in convalescent serum specimens, and in all dose groups the median magnitude after the second vaccination was in the upper quartile of values in the convalescent serum specimens.

The S-2P ELISA GMTs at day 57 (299,751 [95% confidence interval {CI}, 206,071 to 436,020] in the 25-μg group, 782,719 [95% viagra 100 CI, 619,310 to 989,244] in the 100-μg group, and 1,192,154 [95% CI, 924,878 to 1,536,669] in the 250-μg group) exceeded that in the convalescent serum specimens (142,140 [95% CI, 81,543 to 247,768]). erectile dysfunction Neutralization Responses No participant had detectable PsVNA responses before vaccination. After the first vaccination, PsVNA responses were viagra 100 detected in less than half the participants, and a dose effect was seen (50% inhibitory dilution [ID50].

Figure 2C, Fig. S8, and Table 2. 80% inhibitory dilution [ID80] viagra 100.

Fig. S2 and Table S6) viagra 100. However, after the second vaccination, PsVNA responses were identified in serum samples from all participants.

The lowest responses were in the 25-μg dose group, with a geometric mean ID50 of 112.3 viagra 100 (95% CI, 71.2 to 177.1) at day 43. The higher responses in the 100-μg and 250-μg groups were similar in magnitude (geometric mean ID50, 343.8 [95% CI, 261.2 to 452.7] and 332.2 [95% CI, 266.3 to 414.5], respectively, at day 43). These responses were viagra 100 similar to values in the upper half of the distribution of values for convalescent serum specimens.

Before vaccination, no participant had detectable 80% live-viagra neutralization at the highest serum concentration tested (1:8 dilution) in the PRNT assay. At day 43, wild-type viagra–neutralizing activity capable of reducing erectile dysfunction infectivity by 80% or more (PRNT80) was detected in all participants, with geometric mean PRNT80 responses of 339.7 (95% CI, 184.0 to 627.1) in the 25-μg group and 654.3 (95% CI, 460.1 to 930.5) in the 100-μg group (Figure 2D). Neutralizing PRNT80 average responses were generally at or above the values of the three convalescent serum specimens tested in viagra 100 this assay.

Good agreement was noted within and between the values from binding assays for S-2P and receptor-binding domain and neutralizing activity measured by PsVNA and PRNT (Figs. S3 through S7), which provides orthogonal support for each assay in characterizing the humoral response induced viagra 100 by mRNA-1273. erectile dysfunction T-Cell Responses The 25-μg and 100-μg doses elicited CD4 T-cell responses (Figs.

S9 and S10) that on stimulation by S-specific peptide pools were strongly biased toward expression of Th1 cytokines (tumor necrosis viagra 100 factor α >. Interleukin 2 >. Interferon γ), with minimal type viagra 100 2 helper T-cell (Th2) cytokine expression (interleukin 4 and interleukin 13).

CD8 T-cell responses to S-2P were detected at low levels after the second vaccination in the 100-μg dose group (Fig. S11)..

Patients Figure 1 online viagra cost. Figure 1. Enrollment and online viagra cost Randomization.

Of the 1114 patients who were assessed for eligibility, 1062 underwent randomization. 541 were assigned to the online viagra cost remdesivir group and 521 to the placebo group (intention-to-treat population) (Figure 1). 159 (15.0%) were categorized as having mild-to-moderate disease, and 903 (85.0%) were in the severe disease stratum.

Of those assigned to receive remdesivir, 531 patients (98.2%) received online viagra cost the treatment as assigned. Fifty-two patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death and 10 withdrew consent. Of those assigned to receive placebo, 517 patients (99.2%) received placebo online viagra cost as assigned.

Seventy patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death and 14 withdrew consent. A total of 517 patients in the remdesivir group and 508 in the placebo group completed the trial through day 29, recovered, or died. Fourteen patients who received remdesivir and 9 who received placebo terminated online viagra cost their participation in the trial before day 29.

A total of 54 of the patients who were in the mild-to-moderate stratum at randomization were subsequently determined to meet the criteria for severe disease, resulting in 105 patients in the mild-to-moderate disease stratum and 957 in the severe stratum. The as-treated population included 1048 patients who received the assigned treatment (532 in online viagra cost the remdesivir group, including one patient who had been randomly assigned to placebo and received remdesivir, and 516 in the placebo group). Table 1.

Table 1 online viagra cost. Demographic and Clinical Characteristics of the Patients at Baseline. The mean age of the patients was 58.9 years, and online viagra cost 64.4% were male (Table 1).

On the basis of the evolving epidemiology of erectile dysfunction treatment during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1 in the Supplementary Appendix). Overall, 53.3% of the patients were White, 21.3% were Black, 12.7% were Asian, and 12.7% were designated as other or not reported. 250 (23.5%) online viagra cost were Hispanic or Latino.

Most patients had either one (25.9%) or two or more (54.5%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (50.2%), obesity (44.8%), and type 2 diabetes mellitus (30.3%). The median number of days between symptom onset online viagra cost and randomization was 9 (interquartile range, 6 to 12) (Table S2). A total of 957 patients (90.1%) had severe disease at enrollment.

285 patients (26.8%) met category 7 criteria online viagra cost on the ordinal scale, 193 (18.2%) category 6, 435 (41.0%) category 5, and 138 (13.0%) category 4. Eleven patients (1.0%) had missing ordinal scale data at enrollment. All these online viagra cost patients discontinued the study before treatment.

During the study, 373 patients (35.6% of the 1048 patients in the as-treated population) received hydroxychloroquine and 241 (23.0%) received a glucocorticoid (Table S3). Primary Outcome Figure 2 online viagra cost. Figure 2.

Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates are shown in the overall population (Panel A), in patients with a baseline score of 4 on the ordinal online viagra cost scale (not receiving oxygen. Panel B), in those with a baseline score of 5 (receiving oxygen.

Panel C), online viagra cost in those with a baseline score of 6 (receiving high-flow oxygen or noninvasive mechanical ventilation. Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or extracorporeal membrane oxygenation [ECMO]. Panel E).Table 2 online viagra cost.

Table 2. Outcomes Overall and According to Score on the Ordinal Scale in the online viagra cost Intention-to-Treat Population. Figure 3.

Figure 3. Time to Recovery According online viagra cost to Subgroup. The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects.

Race and ethnic group were reported by the patients.Patients in the remdesivir group had a shorter time to recovery than patients in the placebo group (median, online viagra cost 10 days, as compared with 15 days. Rate ratio for recovery, 1.29. 95% confidence interval [CI], 1.12 to online viagra cost 1.49.

P<0.001) (Figure 2 and Table 2). In the severe disease stratum (957 patients) the median time to online viagra cost recovery was 11 days, as compared with 18 days (rate ratio for recovery, 1.31. 95% CI, 1.12 to 1.52) (Table S4).

The rate online viagra cost ratio for recovery was largest among patients with a baseline ordinal score of 5 (rate ratio for recovery, 1.45. 95% CI, 1.18 to 1.79). Among patients with a baseline score of 4 and those with a baseline score of 6, the rate ratio estimates for recovery were 1.29 (95% CI, 0.91 to 1.83) and 1.09 (95% CI, 0.76 to 1.57), respectively.

For those receiving mechanical ventilation or ECMO online viagra cost at enrollment (baseline ordinal score of 7), the rate ratio for recovery was 0.98 (95% CI, 0.70 to 1.36). Information on interactions of treatment with baseline ordinal score as a continuous variable is provided in Table S11. An analysis adjusting for baseline ordinal score as a covariate was conducted to evaluate the online viagra cost overall effect (of the percentage of patients in each ordinal score category at baseline) on the primary outcome.

This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.26. 95% CI, 1.09 online viagra cost to 1.46). Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.37 (95% CI, 1.14 to 1.64), whereas patients who underwent randomization more than 10 days after the onset of symptoms had a rate ratio for recovery of 1.20 (95% CI, 0.94 to 1.52) (Figure 3).

The benefit of remdesivir was larger when given earlier in the illness, though the benefit online viagra cost persisted in most analyses of duration of symptoms (Table S6). Sensitivity analyses in which data were censored at earliest reported use of glucocorticoids or hydroxychloroquine still showed efficacy of remdesivir (9.0 days to recovery with remdesivir vs. 14.0 days to recovery with placebo.

Rate ratio, 1.28 online viagra cost. 95% CI, 1.09 to 1.50, and 10.0 vs. 16.0 days online viagra cost to recovery.

Rate ratio, 1.32. 95% CI, online viagra cost 1.11 to 1.58, respectively) (Table S8). Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as determined by a proportional odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.5.

95% CI, 1.2 to 1.9, adjusted for disease severity) online viagra cost (Table 2 and Fig. S7). Mortality Kaplan–Meier estimates of mortality by day 15 were 6.7% in the remdesivir group and 11.9% in the placebo group (hazard ratio, 0.55.

95% CI, online viagra cost 0.36 to 0.83). The estimates by day 29 were 11.4% and 15.2% in two groups, respectively (hazard ratio, 0.73. 95% CI, 0.52 to 1.03) online viagra cost.

The between-group differences in mortality varied considerably according to baseline severity (Table 2), with the largest difference seen among patients with a baseline ordinal score of 5 (hazard ratio, 0.30. 95% CI, online viagra cost 0.14 to 0.64). Information on interactions of treatment with baseline ordinal score with respect to mortality is provided in Table S11.

Additional Secondary Outcomes Table online viagra cost 3. Table 3. Additional Secondary Outcomes online viagra cost.

Patients in the remdesivir group had a shorter time to improvement of one or of two categories on the ordinal scale from baseline than patients in the placebo group (one-category improvement. Median, 7 vs. 9 days online viagra cost.

Rate ratio for recovery, 1.23. 95% CI, 1.08 to 1.41 online viagra cost. Two-category improvement.

Median, 11 online viagra cost vs. 14 days. Rate ratio, 1.29 online viagra cost.

95% CI, 1.12 to 1.48) (Table 3). Patients in the remdesivir group had a shorter time to discharge or to a National Early Warning Score of 2 or lower than those in the placebo group (median, 8 days vs. 12 days online viagra cost.

Hazard ratio, 1.27. 95% CI, 1.10 to 1.46) online viagra cost. The initial length of hospital stay was shorter in the remdesivir group than in the placebo group (median, 12 days vs.

17 days) online viagra cost. 5% of patients in the remdesivir group were readmitted to the hospital, as compared with 3% in the placebo group. Among the 913 patients receiving oxygen at enrollment, those in the remdesivir group continued to receive oxygen for fewer days than patients in the placebo group (median, 13 days online viagra cost vs.

21 days), and the incidence of new oxygen use among patients who were not receiving oxygen at enrollment was lower in the remdesivir group than in the placebo group (incidence, 36% [95% CI, 26 to 47] vs. 44% [95% CI, 33 online viagra cost to 57]). For the 193 patients receiving noninvasive ventilation or high-flow oxygen at enrollment, the median duration of use of these interventions was 6 days in both the remdesivir and placebo groups.

Among the 573 patients who were not receiving noninvasive ventilation, high-flow oxygen, invasive ventilation, or ECMO at baseline, the incidence of new noninvasive ventilation or high-flow oxygen use was lower in the remdesivir group than in the placebo group (17% [95% CI, 13 to 22] vs. 24% [95% CI, 19 online viagra cost to 30]). Among the 285 patients who were receiving mechanical ventilation or ECMO at enrollment, patients in the remdesivir group received these interventions for fewer subsequent days than those in the placebo group (median, 17 days vs.

20 days), and the incidence of new mechanical ventilation or ECMO use among the 766 patients who were not receiving these interventions at enrollment was lower in the remdesivir online viagra cost group than in the placebo group (13% [95% CI, 10 to 17] vs. 23% [95% CI, 19 to 27]) (Table 3). Safety Outcomes In the as-treated population, serious online viagra cost adverse events occurred in 131 of 532 patients (24.6%) in the remdesivir group and in 163 of 516 patients (31.6%) in the placebo group (Table S17).

There were 47 serious respiratory failure adverse events in the remdesivir group (8.8% of patients), including acute respiratory failure and the need for endotracheal intubation, and 80 in the placebo group (15.5% of patients) (Table S19). No deaths online viagra cost were considered by the investigators to be related to treatment assignment. Grade 3 or 4 adverse events occurred on or before day 29 in 273 patients (51.3%) in the remdesivir group and in 295 (57.2%) in the placebo group (Table S18).

41 events were judged by the investigators to be related to remdesivir and 47 events to placebo (Table S17). The most common nonserious adverse events occurring in at least 5% of all patients included decreased glomerular filtration online viagra cost rate, decreased hemoglobin level, decreased lymphocyte count, respiratory failure, anemia, pyrexia, hyperglycemia, increased blood creatinine level, and increased blood glucose level (Table S20). The incidence of these adverse events was generally similar in the remdesivir and placebo groups.

Crossover After the data and safety monitoring board recommended that the preliminary primary analysis report be provided to the sponsor, data on online viagra cost a total of 51 patients (4.8% of the total study enrollment) — 16 (3.0%) in the remdesivir group and 35 (6.7%) in the placebo group — were unblinded. 26 (74.3%) of those in the placebo group whose data were unblinded were given remdesivir. Sensitivity analyses evaluating the unblinding (patients whose treatment assignments were unblinded had their data online viagra cost censored at the time of unblinding) and crossover (patients in the placebo group treated with remdesivir had their data censored at the initiation of remdesivir treatment) produced results similar to those of the primary analysis (Table S9).Study Design and Participants To reduce the risk of introducing erectile dysfunction into basic training at Marine Corps Recruit Depot, Parris Island, in South Carolina, the Marine Corps established a 14-day supervised quarantine period at a college campus used exclusively for this purpose.

Potential recruits were instructed to quarantine at home for 2 weeks immediately before they traveled to campus. At the end online viagra cost of the second, supervised quarantine on campus, all recruits were required to have a negative qPCR result before they could enter Parris Island. Recruits were asked to participate in the erectile dysfunction treatment Health Action Response for Marines (CHARM) study, which included weekly qPCR testing and blood sampling for IgG antibody assessment.

After potential recruits had completed the 14-day home quarantine, they presented to a local Military Entrance Processing Station, where a medical history was taken and a physical examination was performed. If potential recruits were deemed to be physically and mentally fit for enlistment, they were instructed to wear masks at all times and maintain social distancing of at least 6 feet during travel to the online viagra cost quarantine campus. Classes of 350 to 450 recruits arrived on campus nearly weekly.

New classes were divided into online viagra cost platoons of 50 to 60 recruits, and roommates were assigned independently of participation in the CHARM study. Overlapping classes were housed in different dormitories and had different dining times and training schedules. During the supervised quarantine, public health measures were enforced to suppress erectile dysfunction transmission (Table S1 in the Supplementary Appendix, available with the full text of this article at NEJM.org) online viagra cost.

All recruits wore double-layered cloth masks at all times indoors and outdoors, except when sleeping or eating. Practiced social distancing of at least 6 feet online viagra cost. Were not allowed to leave campus.

Did not have access to personal electronics and other online viagra cost items that might contribute to surface transmission. And routinely washed their hands. They slept in double-occupancy rooms with sinks, ate in shared dining facilities, and used shared bathrooms.

All recruits cleaned their rooms daily, sanitized bathrooms online viagra cost after each use with bleach wipes, and ate preplated meals in a dining hall that was cleaned with bleach after each platoon had eaten. Most instruction and exercises were conducted outdoors. All movement of recruits was supervised, and online viagra cost unidirectional flow was implemented, with designated building entry and exit points to minimize contact among persons.

All recruits, regardless of participation in the study, underwent daily temperature and symptom screening. Six instructors who were assigned to each platoon worked online viagra cost in 8-hour shifts and enforced the quarantine measures. If recruits reported any signs or symptoms consistent with erectile dysfunction treatment, they reported to sick call, underwent rapid qPCR testing for erectile dysfunction, and were placed in isolation pending the results of testing.

Instructors were also restricted to campus, were required to wear masks, were provided with preplated meals, and underwent daily temperature checks online viagra cost and symptom screening. Instructors who were assigned to a platoon in which a positive case was diagnosed underwent rapid qPCR testing for erectile dysfunction, and, if the result was positive, the instructor was removed from duty. Recruits and instructors were prohibited from interacting with campus support staff, such as janitorial and food-service personnel.

After each class completed quarantine, a deep bleach cleaning of surfaces was performed in the bathrooms, showers, bedrooms, and hallways in the online viagra cost dormitories, and the dormitory remained unoccupied for at least 72 hours before reoccupancy. Within 2 days after arrival at the campus, after recruits had received assignments to platoons and roommates, they were offered the opportunity to participate in the longitudinal CHARM study. Recruits were eligible if they were online viagra cost 18 years of age or older and if they would be available for follow-up.

The study was approved by the institutional review board of the Naval Medical Research Center and complied with all applicable federal regulations governing the protection of human subjects. All participants provided written online viagra cost informed consent. Procedures At the time of enrollment, participants answered a questionnaire regarding demographic characteristics, risk factors for erectile dysfunction , symptoms within the previous 14 days, and a brief medical history.

Blood samples and mid-turbinate nares swab specimens were obtained for qPCR online viagra cost testing to detect erectile dysfunction. Demographic information included sex, age, ethnic group, race, place of birth, and U.S. State or online viagra cost country of residence.

Information regarding risk factors included whether participants had used masks, whether they had adhered to self-quarantine before arrival, their recent travel history, their known exposure to someone with erectile dysfunction treatment, whether they had flulike symptoms or other respiratory illness, and whether they had any of 14 specific symptoms characteristic of erectile dysfunction treatment or any other symptoms associated with an unspecified condition within the previous 14 days. Study participants were followed up on days 7 and 14, at which time they reported any symptoms that had occurred within the past 7 days. Nares swab specimens for repeat qPCR online viagra cost assays were also obtained.

Participants who had positive qPCR results were placed in isolation and were approached for participation in a related but separate study of infected recruits, which involved more frequent testing during isolation. All recruits who did not participate in the current study were tested for erectile dysfunction only at the end of the 2-week quarantine, unless clinically indicated online viagra cost (in accordance with the public health procedures of the Marine Corps). Serum specimens obtained at enrollment were tested for erectile dysfunction–specific IgG antibodies with the use of the methods described below and in the Supplementary Appendix.

Participants who tested positive on the day of enrollment (day 0) or on day 7 or day 14 were online viagra cost separated from their roommates and were placed in isolation. Otherwise, participants and nonparticipants were not treated differently. They followed the online viagra cost same safety protocols, were assigned to rooms and platoons regardless of participation in the study, and received the same formal instruction.

Laboratory Methods The qPCR testing of mid-turbinate nares swab specimens for erectile dysfunction was performed within 48 hours after collection by Lab24 (Boca Raton, FL) with the use of the TaqPath erectile dysfunction treatment Combo Kit (Thermo Fisher Scientific), which is authorized by the Food and Drug Administration. Specimens obtained from nonparticipants were tested by the Naval Medical Research Center (Silver Spring, MD). Specimens were online viagra cost stored in viral transport medium at 4°C.

The presence of IgG antibodies specific to the erectile dysfunction receptor-binding (spike) domain in serum specimens was evaluated with the use of an enzyme-linked immunosorbent assay, as previously described,10 with some modifications. At least online viagra cost two positive controls, eight negative controls (serum specimens obtained before July 2019), and four blanks (no serum) were included in every plate. Serum specimens were first screened at a 1:50 dilution, followed by full dilution series if the specimens were initially found to be positive.

Whole-Genome Sequencing and Assembly erectile dysfunction sequencing was performed with the use of two sequencing protocols (an Illumina sequencing protocol and an Ion Torrent sequencing online viagra cost protocol) to increase the likelihood of obtaining complete genome sequences. A custom reference-based analysis pipeline (https://github.com/mjsull/erectile dysfunction treatment_pipe) was used to assemble erectile dysfunction genomes with the use of data from Illumina, Ion Torrent, or both.11 Phylogenetic Analysis erectile dysfunction genomes obtained from patients worldwide and associated metadata were downloaded from the Global Initiative on Sharing All Influenza Data EpiCoV database12 on August 11, 2020 (79,840 sequences), and a subset of sequences was selected from this database with the use of the default subsampling scheme of Nextstrain software13 with the aim of maximizing representation of genomes obtained from patients in the United States. Phylogenetic analyses of the specimens obtained from participants were performed with the v1.0-292-ga9de690 Nextstrain build for erectile dysfunction genomes with the use online viagra cost of default parameters.

Transmission and outbreak events were identified on the basis of clustering of the erectile dysfunction genomes obtained from study participants within the Nextstrain phylogenetic tree, visualized with TreeTime.14 A comparative analysis of mutation profiles relative to the erectile dysfunction Wuhan reference genome was performed with the use of Nextclade software, version 0.3.6 (https://clades.nextstrain.org/). Data Analysis The denominator for calculating the percentage of recruits who had a first positive result for erectile dysfunction by qPCR assay on each day of testing excluded recruits who had previously tested positive, had online viagra cost dropped out of the study, were administratively separated from the Marine Corps, or had missing data. The denominator for calculating the cumulative positivity rates included all recruits who had undergone testing at previous time points, including those who were no longer participating in the study.

Only descriptive numerical results and percentages are reported, with no formal statistical analysis.Trial Population Table 1. Table 1 online viagra cost. Characteristics of the Participants in the mRNA-1273 Trial at Enrollment.

The 45 enrolled participants received their first vaccination between March 16 online viagra cost and April 14, 2020 (Fig. S1). Three participants did not receive the second vaccination, including one in the 25-μg group who had urticaria on both legs, with onset 5 days after the first vaccination, and two (one in the 25-μg group and one in the 250-μg group) who missed the second vaccination window owing to isolation for suspected erectile dysfunction treatment while the online viagra cost test results, ultimately negative, were pending.

All continued to attend scheduled trial visits. The demographic online viagra cost characteristics of participants at enrollment are provided in Table 1. treatment Safety No serious adverse events were noted, and no prespecified trial halting rules were met.

As noted above, one participant in the 25-μg group was withdrawn because of an unsolicited adverse event, transient urticaria, judged to be related to the first vaccination. Figure 1 online viagra cost. Figure 1.

Systemic and online viagra cost Local Adverse Events. The severity of solicited adverse events was graded as mild, moderate, or severe (see Table S1).After the first vaccination, solicited systemic adverse events were reported by 5 participants (33%) in the 25-μg group, 10 (67%) in the 100-μg group, and 8 (53%) in the 250-μg group. All were mild or online viagra cost moderate in severity (Figure 1 and Table S2).

Solicited systemic adverse events were more common after the second vaccination and occurred in 7 of 13 participants (54%) in the 25-μg group, all 15 in the 100-μg group, and all 14 in the 250-μg group, with 3 of those participants (21%) reporting one or more severe events. None of online viagra cost the participants had fever after the first vaccination. After the second vaccination, no participants in the 25-μg group, 6 (40%) in the 100-μg group, and 8 (57%) in the 250-μg group reported fever.

One of the events (maximum temperature, 39.6°C) in the 250-μg group was graded severe. (Additional details regarding adverse events for that participant online viagra cost are provided in the Supplementary Appendix.) Local adverse events, when present, were nearly all mild or moderate, and pain at the injection site was common. Across both vaccinations, solicited systemic and local adverse events that occurred in more than half the participants included fatigue, chills, headache, myalgia, and pain at the injection site.

Evaluation of safety clinical laboratory values of grade 2 or higher and unsolicited online viagra cost adverse events revealed no patterns of concern (Supplementary Appendix and Table S3). erectile dysfunction Binding Antibody Responses Table 2. Table 2 online viagra cost.

Geometric Mean Humoral Immunogenicity Assay Responses to mRNA-1273 in Participants and in Convalescent Serum Specimens. Figure 2 online viagra cost. Figure 2.

erectile dysfunction Antibody online viagra cost and Neutralization Responses. Shown are geometric mean reciprocal end-point enzyme-linked immunosorbent assay (ELISA) IgG titers to S-2P (Panel A) and receptor-binding domain (Panel B), PsVNA ID50 responses (Panel C), and live viagra PRNT80 responses (Panel D). In Panel A and Panel B, boxes and horizontal bars denote interquartile range (IQR) and median area under the curve (AUC), respectively.

Whisker endpoints are equal to the maximum and online viagra cost minimum values below or above the median ±1.5 times the IQR. The convalescent serum panel includes specimens from 41 participants. Red dots indicate the 3 specimens online viagra cost that were also tested in the PRNT assay.

The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent serum panel. In Panel C, boxes and horizontal bars denote online viagra cost IQR and median ID50, respectively. Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR.

In the convalescent serum panel, online viagra cost red dots indicate the 3 specimens that were also tested in the PRNT assay. The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent panel. In Panel D, boxes and horizontal bars denote IQR and median PRNT80, respectively.

Whisker end online viagra cost points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR. The three convalescent serum specimens were also tested in ELISA and PsVNA assays. Because of the time-intensive nature of the PRNT assay, for this preliminary report, PRNT results were available only for the 25-μg and 100-μg dose groups.Binding antibody IgG geometric mean titers (GMTs) to S-2P increased rapidly after the first vaccination, with seroconversion in all participants by online viagra cost day 15 (Table 2 and Figure 2A).

Dose-dependent responses to the first and second vaccinations were evident. Receptor-binding domain–specific antibody responses were similar in pattern and magnitude (Figure online viagra cost 2B). For both assays, the median magnitude of antibody responses after the first vaccination in the 100-μg and 250-μg dose groups was similar to the median magnitude in convalescent serum specimens, and in all dose groups the median magnitude after the second vaccination was in the upper quartile of values in the convalescent serum specimens.

The S-2P ELISA GMTs at day 57 (299,751 [95% confidence interval {CI}, 206,071 to 436,020] in the 25-μg group, 782,719 [95% CI, 619,310 to 989,244] in the 100-μg group, and 1,192,154 [95% CI, 924,878 to 1,536,669] in the 250-μg group) exceeded online viagra cost that in the convalescent serum specimens (142,140 [95% CI, 81,543 to 247,768]). erectile dysfunction Neutralization Responses No participant had detectable PsVNA responses before vaccination. After the first vaccination, PsVNA responses were detected in less than half the participants, and a dose effect was seen (50% inhibitory online viagra cost dilution [ID50].

Figure 2C, Fig. S8, and Table 2. 80% inhibitory online viagra cost dilution [ID80].

Fig. S2 and online viagra cost Table S6). However, after the second vaccination, PsVNA responses were identified in serum samples from all participants.

The lowest responses were in the 25-μg dose group, with a geometric mean ID50 online viagra cost of 112.3 (95% CI, 71.2 to 177.1) at day 43. The higher responses in the 100-μg and 250-μg groups were similar in magnitude (geometric mean ID50, 343.8 [95% CI, 261.2 to 452.7] and 332.2 [95% CI, 266.3 to 414.5], respectively, at day 43). These responses were similar to values in the upper half online viagra cost of the distribution of values for convalescent serum specimens.

Before vaccination, no participant had detectable 80% live-viagra neutralization at the highest serum concentration tested (1:8 dilution) in the PRNT assay. At day 43, wild-type viagra–neutralizing activity capable of reducing erectile dysfunction infectivity by 80% or more (PRNT80) was detected in all participants, with geometric mean PRNT80 responses of 339.7 (95% CI, 184.0 to 627.1) in the 25-μg group and 654.3 (95% CI, 460.1 to 930.5) in the 100-μg group (Figure 2D). Neutralizing PRNT80 average responses were generally at or above the values of the three online viagra cost convalescent serum specimens tested in this assay.

Good agreement was noted within and between the values from binding assays for S-2P and receptor-binding domain and neutralizing activity measured by PsVNA and PRNT (Figs. S3 through S7), which provides orthogonal support for each assay in online viagra cost characterizing the humoral response induced by mRNA-1273. erectile dysfunction T-Cell Responses The 25-μg and 100-μg doses elicited CD4 T-cell responses (Figs.

S9 and S10) that on online viagra cost stimulation by S-specific peptide pools were strongly biased toward expression of Th1 cytokines (tumor necrosis factor α >. Interleukin 2 >. Interferon γ), with minimal type 2 helper T-cell (Th2) online viagra cost cytokine expression (interleukin 4 and interleukin 13).

CD8 T-cell responses to S-2P were detected at low levels after the second vaccination in the 100-μg dose group (Fig. S11)..

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