Writing Committee for the REMAP-CAP Investigators IMPORTANCE The evidence for benefit of convalescent plasma for critically ill patients with COVID-19 is inconclusive.OBJECTIVE To determine whether convalescent plasma would improve outcomes for critically ill adults with COVID-19. DESIGN, SETTING, AND PARTICIPANTSThe ongoing Randomized, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia (REMAP-CAP) enrolled and randomized 4763 adults with suspected or confirmed COVID-19 between March 9, 2020, and January 18, 2021, within at least 1 domain; 2011 critically ill adults were randomized to open-label interventions in the immunoglobulin domain at 129 sites in 4 countries. Follow-up ended on April 19, 2021. INTERVENTIONSThe immunoglobulin domain randomized participants to receive 2 units of high-titer, ABO-compatible convalescent plasma (total volume of 550 mL ± 150 mL) within 48 hours of randomization (n = 1084) or no convalescent plasma (n = 916). MAIN OUTCOMES AND MEASURESThe primary ordinal end point was organ support-free days (days alive and free of intensive care unit-based organ support) up to day 21 (range, −1 to 21 days; patients who died were assigned -1 day). The primary analysis was an adjusted bayesian cumulative logistic model. Superiority was defined as the posterior probability of an odds ratio (OR) greater than 1 (threshold for trial conclusion of superiority >99%). Futility was defined as the posterior probability of an OR less than 1.2 (threshold for trial conclusion of futility >95%). An OR greater than 1 represented improved survival, more organ support-free days, or both. The prespecified secondary outcomes included in-hospital survival; 28-day survival; 90-day survival; respiratory support-free days; cardiovascular support-free days; progression to invasive mechanical ventilation, extracorporeal mechanical oxygenation, or death; intensive care unit length of stay; hospital length of stay; World Health Organization ordinal scale score at day 14; venous thromboembolic events at 90 days; and serious adverse events. RESULTS Among the 2011 participants who were randomized (median age, 61 [IQR, 52 to 70] years and 645/1998 [32.3%] women), 1990 (99%) completed the trial. The convalescent plasma intervention was stopped after the prespecified criterion for futility was met. The median number of organ support-free days was 0 (IQR, -1 to 16) in the convalescent plasma group and 3 (IQR, -1 to 16) in the no convalescent plasma group. The in-hospital mortality rate was 37.3% (401/1075) for the convalescent plasma group and 38.4% (347/904) for the no convalescent plasma group and the median number of days alive and free of organ support was 14 (IQR, 3 to 18) and 14 (IQR, 7 to 18), respectively. The median-adjusted OR was 0.97 (95% credible interval, 0.83 to 1.15) and the posterior probability of futility (OR <1.2) was 99.4% for the convalescent plasma group compared with the no convalescent plasma group. The treatment effects were consistent across the primary outcome and the 11...

Background.Overweight and obesity have negative health effects. Primary care clinicians are best placed to intervene in weight management. Previous reviews of weight loss interventions have included studies from specialist settings. The aim of this review was to estimate the effect of behavioural interventions delivered in primary care on body weight in overweight and obese adults.Methods.The review included randomized controlled trials (RCTs) of behavioural interventions in obese or overweight adult participants in a primary care setting, with weight loss as the primary outcome, and a minimum of 12 months of follow-up. A systematic search strategy was implemented in Medline, Embase, Web of Science and the Cochrane Central Registry of Controlled Trials. Risk of bias was assessed using the Cochrane Risk of Bias tool and behavioural science components of interventions were evaluated. Data relating to weight loss in kilograms were extracted, and the results combined using meta-analysis.Results.Fifteen RCTs, with 4539 participants randomized, were selected for inclusion. The studies were heterogeneous with respect to inclusion criteria and type of intervention. Few studies reported interventions informed by behavioural science theory. Pooled results from meta-analysis indicated a mean weight loss of −1.36kg (−2.10 to −0.63, P < 0.0001) at 12 months, and −1.23kg (−2.28 to −0.18, P = 0.002) at 24 months.Conclusion.Behavioural weight loss interventions in primary care yield very small reductions in body weight, which are unlikely to be clinically significant. More effective management strategies are needed for the treatment of overweight and obesity.

Background Health checks are promoted to evaluate individuals' risk of developing disease and to initiate health promotion and disease prevention interventions. The NHS Health Check is a cardiovascular risk assessment programme introduced in the UK aimed at preventing cardiovascular disease (CVD). Uptake of health checks is lower than anticipated. This study aimed to explore influences on people's decisions to take up the offer of a health check.

Purpose: Much concern has been expressed that feedback of personalized genetic risk information may lead to fatalism, i.e., a lack of perceived control over the risk. This review aimed to assess the strength of evidence for such a view. Method: Electronic databases were searched to find eligible studies, which comprised randomized, controlled trials and analog studies, in which participants in one arm received either real or imagined personalized genetic risk information and assessed perceived control in relation to the treatability or preventability of the health problem. Results: Inspection of 1340 abstracts resulted in 5 studies meeting the inclusion criteria, involving the prediction of obesity, heart disease, depression, and diabetes. Meta-analyses of the clinical studies revealed no impact of personalized genetic risk information on perceived control in either the short term (pooled standardized mean difference 0.09, 95% confidence interval, Ϫ0.51 to 0.70) or longer term (pooled standardized mean difference 0.00, confidence interval, Ϫ0.20 to 0.21). Similarly, no impact on perceived control was evident in the three analog studies (pooled standardized mean difference 0.02, confidence interval, Ϫ0.17 to 0.20). Conclusion: Few studies have assessed empirically the impact of personalized genetic risk information on fatalism, assessed using perceptions of control over the risk. Limited evidence suggests feedback of genetic risk information may have little impact on such beliefs. Genet Med 2011: 13(4):273-277.

Objectives: To examine the consequences of informing smokers of a genetic predisposition to nicotine dependence and of providing treatment efficacy information tailored to genetic status. Design: Analogue study using four vignettes; 2 (genetic status) × 2 (whether treatment efficacy information provided) between subjects design. Participants: 269 British adult smokers. Outcome measures: Preferred cessation methods and perceived control over quitting. Results: Gene positive participants were significantly more likely to choose the cessation method described as effective for their genetic status, but significantly less likely to choose to use their own willpower. Providing tailored treatment information did not alter these effects. Perceived control was not significantly affected by either genetic status or information provision. Conclusions: Learning of a genetic predisposition to nicotine dependence may increase desire for effective cessation methods, but may undermine the perceived importance of willpower in stopping smoking. There is growing interest in identifying genetic markers that predict a heightened risk of nicotine dependence.1 2 A recent review suggested that the most likely benefit of this research would be an improvement in smoking cessation rates, achieved by tailoring cessation interventions to a smoker's genetic profile.1 However, it is important to consider whether telling smokers that they are genetically predisposed to nicotine dependence will make them believe that their nicotine dependence is intractable. Research into reactions to genetic testing has largely focused on testing predictive of disease risk.3 Two studies have examined the impact on smokers' quitting behaviours of learning of a genetic vulnerability to lung cancer. The provision of high risk information did not increase cessation rates. [4][5][6] It is possible that genetic testing predictive of cessation treatment response may more effectively promote smoking cessation than genetic risk information predictive of disease susceptibility. Genetic risks are sometimes seen as immutable and may engender a sense of fatalism.7 Given that perceived control is an important predictor of motivation for, and actual, addictive behaviour change, 8 learning one has a genetic predisposition to nicotine dependence could adversely affect quitting.Clinicians also need to know how the provision of information regarding genetic predisposition to dependence will affect smokers' choice of cessation methods. An individual's perception of a health problem, including its causes, influences their coping actions.9 Telling individuals that they have a genetic predisposition to nicotine dependence should influence actions taken to stop smoking. Clinicians can take advantage of this relation between perceived causes and actions by providing information about cessation methods particularly suited to those with a genetic predisposition to nicotine dependence.As research on this topic is at an early stage, smokers are not yet being offered information on their g...