Testosterone therapy is increasingly promoted. No randomized placebo-controlled trial has been implemented to assess the effect of testosterone therapy on cardiovascular events, although very high ...levels of androgens are thought to promote cardiovascular disease.
A systematic review and meta-analysis was conducted of placebo-controlled randomized trials of testosterone therapy among men lasting 12+ weeks reporting cardiovascular-related events. We searched PubMed through the end of 2012 using "("testosterone" or "androgen") and trial and ("random*")" with the selection limited to studies of men in English, supplemented by a bibliographic search of the World Health Organization trial registry. Two reviewers independently searched, selected and assessed study quality with differences resolved by consensus. Two statisticians independently abstracted and analyzed data, using random or fixed effects models, as appropriate, with inverse variance weighting.
Of 1,882 studies identified 27 trials were eligible including 2,994, mainly older, men who experienced 180 cardiovascular-related events. Testosterone therapy increased the risk of a cardiovascular-related event (odds ratio (OR) 1.54, 95% confidence interval (CI) 1.09 to 2.18). The effect of testosterone therapy varied with source of funding (P-value for interaction 0.03), but not with baseline testosterone level (P-value for interaction 0.70). In trials not funded by the pharmaceutical industry the risk of a cardiovascular-related event on testosterone therapy was greater (OR 2.06, 95% CI 1.34 to 3.17) than in pharmaceutical industry funded trials (OR 0.89, 95% CI 0.50 to 1.60).
The effects of testosterone on cardiovascular-related events varied with source of funding. Nevertheless, overall and particularly in trials not funded by the pharmaceutical industry, exogenous testosterone increased the risk of cardiovascular-related events, with corresponding implications for the use of testosterone therapy.
Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, ...including serial interval distributions-i.e., the time between illness onset in successive cases in a transmission chain-and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 shortened substantially from 7.8 to 2.6 days within a month (9 January to 13 February 2020). This change was driven by enhanced nonpharmaceutical interventions, particularly case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve our ability to assess transmission dynamics, forecast future incidence, and estimate the impact of control measures.
The comparative performance of different clinical sampling methods for diagnosis of SARS-CoV-2 infection by RT-PCR among populations with suspected infection remains unclear. This meta-analysis aims ...to systematically compare the diagnostic performance of different clinical specimen collection methods.
In this systematic review and meta-analysis, we systematically searched PubMed, Embase, MEDLINE, Web of Science, medRxiv, bioRxiv, SSRN, and Research Square from Jan 1, 2000, to Nov 16, 2020. We included original clinical studies that examined the performance of nasopharyngeal swabs and any additional respiratory specimens for the diagnosis of SARS-CoV-2 infection among individuals presenting in ambulatory care. Studies without data on paired samples, or those that only examined different samples from confirmed SARS-CoV-2 cases were not useful for examining diagnostic performance of a test and were excluded. Diagnostic performance, including sensitivity, specificity, positive predictive value, and negative predictive value, was examined using random effects models and double arcsine transformation.
Of the 5577 studies identified in our search, 23 studies including 7973 participants with 16 762 respiratory samples were included. Respiratory specimens examined in these studies included 7973 nasopharyngeal swabs, 1622 nasal swabs, 6110 saliva samples, 338 throat swabs, and 719 pooled nasal and throat swabs. Using nasopharyngeal swabs as the gold standard, pooled nasal and throat swabs gave the highest sensitivity of 97% (95% CI 93–100), whereas lower sensitivities were achieved by saliva (85%, 75–93) and nasal swabs (86%, 77–93) and a much lower sensitivity by throat swabs (68%, 35–94). A comparably high positive predictive value was obtained by pooled nasal and throat (97%, 90–100) and nasal swabs (96%, 87–100) and a slightly lower positive predictive value by saliva (93%, 88–97). Throat swabs have the lowest positive predictive value of 75% (95% CI 45–96). Comparably high specificities (range 97–99%) and negative predictive value (range 95–99%) were observed among different clinical specimens. Comparison between health-care-worker collection and self-collection for pooled nasal and throat swabs and nasal swabs showed comparable diagnostic performance. No significant heterogeneity was observed in the analysis of pooled nasal and throat swabs and throat swabs, whereas moderate to substantial heterogeneity (I2 ≥30%) was observed in studies on saliva and nasal swabs.
Our review suggests that, compared with the gold standard of nasopharyngeal swabs, pooled nasal and throat swabs offered the best diagnostic performance of the alternative sampling approaches for diagnosis of SARS-CoV-2 infection in ambulatory care. Saliva and nasal swabs gave comparable and very good diagnostic performance and are clinically acceptable alternative specimen collection methods. Throat swabs gave a much lower sensitivity and positive predictive value and should not be recommended. Self-collection for pooled nasal and throat swabs and nasal swabs was not associated with any significant impairment of diagnostic accuracy. Our results also provide a useful reference framework for the proper interpretation of SARS-CoV-2 testing results using different clinical specimens.
Hong Kong Research Grants Council.
Influenza viruses undergo frequent antigenic changes. As a result, the viruses circulating change within and between seasons, and the composition of the influenza vaccine is updated annually. Thus, ...estimation of the vaccine's effectiveness is not constant across seasons. In order to provide annual estimates of the influenza vaccine's effectiveness, health departments have increasingly adopted the "test-negative design," using enhanced data from routine surveillance systems. In this design, patients presenting to participating general practitioners with influenza-like illness are swabbed for laboratory testing; those testing positive for influenza virus are defined as cases, and those testing negative form the comparison group. Data on patients' vaccination histories and confounder profiles are also collected. Vaccine effectiveness is estimated from the odds ratio comparing the odds of testing positive for influenza among vaccinated patients and unvaccinated patients, adjusting for confounders. The test-negative design is purported to reduce bias associated with confounding by health-care-seeking behavior and misclassification of cases. In this paper, we use directed acyclic graphs to characterize potential biases in studies of influenza vaccine effectiveness using the test-negative design. We show how studies using this design can avoid or minimize bias and where bias may be introduced with particular study design variations.
Vaccination was a core component for mitigating the 2009 influenza pandemic (pH1N1). However, a vaccination program's efficacy largely depends on population compliance. We examined general population ...decision-making for pH1N1 vaccination using a modified Theory of Planned Behaviour (TBP).
We conducted a longitudinal study, collecting data before and after the introduction of pH1N1 vaccine in Hong Kong. Structural equation modeling (SEM) tested if a modified TPB had explanatory utility for vaccine uptake among adults.
Among 896 subjects who completed both the baseline and the follow-up surveys, 7% (67/896) reported being "likely/very likely/certain" to be vaccinated (intent) but two months later only 0.8% (7/896) reported having received pH1N1 vaccination. Perception of low risk from pH1N1 (60%) and concerns regarding adverse effects of the vaccine (37%) were primary justifications for avoiding pH1N1 vaccination. Greater perceived vaccine benefits (β = 0.15), less concerns regarding vaccine side-effects (β = -0.20), greater adherence to social norms of vaccination (β = 0.39), anticipated higher regret if not vaccinated (β = 0.47), perceived higher self-efficacy for vaccination (β = 0.12) and history of seasonal influenza vaccination (β = 0.12) were associated with higher intention to receive the pH1N1 vaccine, which in turn predicted self-reported vaccination uptake (β = 0.30). Social norm (β = 0.70), anticipated regret (β = 0.19) and vaccination intention (β = 0.31) were positively associated with, and accounted for 70% of variance in vaccination planning, which, in turn subsequently predicted self-reported vaccination uptake (β = 0.36) accounting for 36% of variance in reported vaccination behaviour.
Perceived low risk from pH1N1 and perceived high risk from pH1N1 vaccine inhibited pH1N1 vaccine uptake. Both the TPB and the additional components contributed to intended vaccination uptake but social norms and anticipated regret predominantly associated with vaccination intention and planning. Vaccination planning is a more significant proximal determinant of uptake of pH1N1 vaccine than is intention. Intention alone is an unreliable predictor of future vaccine uptake.
Annual epidemics of seasonal influenza cause hundreds of thousands of deaths, high levels of morbidity, and substantial economic loss. Yet, global influenza circulation has been heavily suppressed by ...public health measures and travel restrictions since the onset of the COVID-19 pandemic. Notably, the influenza B/Yamagata lineage has not been conclusively detected since April 2020, and A(H3N2), A(H1N1), and B/Victoria viruses have since circulated with considerably less genetic diversity. Travel restrictions have largely confined regional outbreaks of A(H3N2) to South and Southeast Asia, B/Victoria to China, and A(H1N1) to West Africa. Seasonal influenza transmission lineages continue to perish globally, except in these select hotspots, which will likely seed future epidemics. Waning population immunity and sporadic case detection will further challenge influenza vaccine strain selection and epidemic control. We offer a perspective on the potential short- and long-term evolutionary dynamics of seasonal influenza and discuss potential consequences and mitigation strategies as global travel gradually returns to pre-pandemic levels.
Abstract
Considerable debates about the general community use of face masks for protection against coronavirus disease 2019 (COVID-19) stemmed out from differing views taken by health authorities. ...Misconceptions and stigmatization towards the use of face masks may hinder the containment of the COVID-19 pandemic. We address this previous debate by analyzing the advice on the community use of masks across different credible health authorities: countries that promoted the use of masks acknowledged that masks are effective but also explained the importance of their proper use along with other hygiene measures. In contrast, authorities that recommended against the community use of masks mainly cited shortage of supplies, the argument that the public do not have the adequate skills to wear them, or that wearing masks might reduce compliance with other important behaviors. We suggest promoting effective behavioral changes in personal protective measures by teaching microbiological knowledge instead of just listing out the “do’s-and-don’ts.”
Debates on community use of face masks against coronavirus disease 2019 (COVID-19) stemmed out from differing views by health authorities, resulting in strong misconceptions and stigmatization. Effective behavioral changes in personal protective measures are required by teaching microbiological knowledge, not just the “do’s-and-don’ts.”
There were 3 influenza pandemics in the 20th century, and there has been 1 so far in the 21st century. Local, national, and international health authorities regularly update their plans for ...mitigating the next influenza pandemic in light of the latest available evidence on the effectiveness of various control measures in reducing transmission. Here, we review the evidence base on the effectiveness of nonpharmaceutical personal protective measures and environmental hygiene measures in nonhealthcare settings and discuss their potential inclusion in pandemic plans. Although mechanistic studies support the potential effect of hand hygiene or face masks, evidence from 14 randomized controlled trials of these measures did not support a substantial effect on transmission of laboratory-confirmed influenza. We similarly found limited evidence on the effectiveness of improved hygiene and environmental cleaning. We identified several major knowledge gaps requiring further research, most fundamentally an improved characterization of the modes of person-to-person transmission.
Cowling and Leung examine the global coronavirus outbreak and the epidemiological research priorities for public health control of the disease. Chinese health authorities announced the discovery of a ...novel coronavirus (2019-nCoV) causing a cluster of pneumonia cases in Wuhan, the major transport hub of central China. The earliest human infections had occurred by early December 2019, and a large wet market in central Wuhan was linked to most, but not all, of the initial cases. There are a number of urgent research priorities to inform the public health response to the infections. Establishing robust estimates of the clinical severity of infections is probably the most pressing, because flattening out the surge in hospital admissions would be essential if there is a danger of hospitals becoming overwhelmed with patients who require inpatient care, not only for those infected with 2019-nCoV but also for urgent acute care of patients with other conditions.
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