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There is growing evidence that racial and ethnic minorities bear a disproportionate burden from COVID-19. Temporal changes in the pandemic epidemiology and diversity in the clinical course require careful study to identify determinants of poor outcomes. We analyzed 6255 hospitalized individuals with PCR-confirmed SARS-CoV-2 infection from one of 5 hospitals in the University of Pennsylvania Health System between March 2020 and March 2021, using electronic health records to assess risk factors and outcomes through 8 weeks post-admission. Discharge, readmission and mortality outcomes were analyzed in a multi-state model with multivariable Cox models for each transition. Mortality varied markedly over time, with cumulative incidence (95% CI) 30 days post-admission of 19.1% (16.9, 21.3) in March-April 2020, 5.7% (4.2, 7.5) in July-October 2020 and 10.5% (9.1,12.0) in January-March 2021; 26% of deaths occurred after discharge. Average age (SD) at admission varied from 62.7 (17.6) to 54.8 (19.9) to 60.5 (18.1); mechanical ventilation use declined from 21.3% to 9–11%. Compared to Caucasian, Black race was associated with more severe disease at admission, higher rates of co-morbidities and residing in a low-income zip code. Between-race risk differences in mortality risk diminished in multivariable models; while admitting hospital, increasing age, admission early in the pandemic, and severe disease and low blood pressure at admission were associated with increased mortality hazard. Hispanic ethnicity was associated with fewer baseline co-morbidities and lower mortality hazard (0.57, 95% CI: 0.37, .087). Multi-state modeling allows for a unified framework to analyze multiple outcomes throughout the disease course. Morbidity and mortality for hospitalized COVID-19 patients varied over time but post-discharge mortality remained non-trivial. Black race was associated with more risk factors for morbidity and with treatment at hospitals with lower mortality. Multivariable models suggest there are not between-race differences in outcomes. Future work is needed to better understand the identified between-hospital differences in mortality.

Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital. In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA, USA. Eligible participants were adults aged 18 years or older who were in hospital with stage 1 or greater acute kidney injury as defined by Kidney Disease Improving Global Outcomes creatinine-based criteria. Exclusion criteria were initial hospital creatinine 4·0 mg/dL (to convert to μmol/L, multiply by 88·4) or greater, fewer than two creatinine values measured, inability to determine the covering provider, admission to hospice or the observation unit, previous randomisation, or end-stage renal disease. Patients were randomly assigned (1:1) via a computer-generated sequence to receive an acute kidney injury alert (a text-based alert sent to the covering provider and unit pharmacist indicating new acute kidney injury) or usual care, stratified by medical versus surgical admission and intensive care unit versus non-intensive care unit location in blocks of 4–8 participants. The primary outcome was a composite of relative maximum change in creatinine, dialysis, and death at 7 days after randomisation. All analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01862419. Between Sept 17, 2013, and April 14, 2014, 23 664 patients were screened. 1201 eligible participants were assigned to the acute kidney injury alert group and 1192 were assigned to the usual care group. Composite relative maximum change in creatinine, dialysis, and death at 7 days did not differ between the alert group and the usual care group (p=0·88), or within any of the four randomisation strata (all p>0·05). At 7 days after randomisation, median maximum relative change in creatinine concentrations was 0·0% (IQR 0·0–18·4) in the alert group and 0·6% (0·0–17·5) in the usual care group (p=0·81); 87 (7·2%) patients in the alert group and 70 (5·9%) patients in usual care group had received dialysis (odds ratio 1·25 [95% CI 0·90–1·74]; p=0·18); and 71 (5·9%) patients in the alert group and 61 (5·1%) patients in the usual care group had died (1·16 [0·81–1·68]; p=0·40). An electronic alert system for acute kidney injury did not improve clinical outcomes among patients in hospital. Penn Center for Healthcare Improvement and Patient Safety.

Abstract Context Studies of the possible cardiovascular risk of testosterone treatment are inconclusive. Objective To determine the effect of testosterone treatment on cardiovascular biomarkers in older men with low testosterone. Design Double-blind, placebo-controlled trial. Setting Twelve academic medical centers in the United States. Participants In all, 788 men ≥65 years old with an average of two serum testosterone levels <275 ng/dL who were enrolled in The Testosterone Trials. Intervention Testosterone gel, the dose adjusted to maintain the testosterone level in the normal range for young men, or placebo gel for 12 months. Main Outcome Measures Serum markers of cardiovascular risk, including lipids and markers of glucose metabolism, fibrinolysis, inflammation, and myocardial damage. Results Compared with placebo, testosterone treatment significantly decreased total cholesterol (adjusted mean difference, −6.1 mg/dL; P < 0.001), high-density lipoprotein cholesterol (adjusted mean difference, −2.0 mg/dL; P < 0.001), and low-density lipoprotein cholesterol (adjusted mean difference, −2.3 mg/dL; P = 0.051) from baseline to month 12. Testosterone also slightly but significantly decreased fasting insulin (adjusted mean difference, −1.7 µIU/mL; P = 0.02) and homeostatic model assessment‒insulin resistance (adjusted mean difference, −0.6; P = 0.03). Testosterone did not change triglycerides, d-dimer, C-reactive protein, interleukin 6, troponin, glucose, or hemoglobin A1c levels more than placebo. Conclusions and Relevance Testosterone treatment of 1 year in older men with low testosterone was associated with small reductions in cholesterol and insulin but not with other glucose markers, markers of inflammation or fibrinolysis, or troponin. The clinical importance of these findings is unclear and requires a larger trial of clinical outcomes. Compared with placebo, testosterone treatment of older men with low testosterone was associated with small reductions in total, HDL, and LDL cholesterol and in insulin and HOMA-IR but not glucose.

Premarketing studies of drugs, although large enough to demonstrate efficacy and detect common adverse events, cannot reliably detect an increased incidence of rare adverse events or events with significant latency. For most drugs, only about 500 to 3000 participants are studied, for relatively short durations, before a drug is marketed. Systems for assessment of postmarketing adverse events include spontaneous reports, computerized claims or medical record databases, and formal postmarketing studies. We briefly review the strengths and limitations of each. Postmarketing surveillance is essential for developing a full understanding of the balance between benefits and adverse effects. More work is needed in analysis of data from spontaneous reports of adverse effects and automated databases, design of ad hoc studies, and design of economically feasible large randomized studies.

IntroductionHip fractures occur 1.6 million times each year worldwide, with substantial associated mortality and losses of independence. At present, anaesthesia care for hip fracture surgery varies widely within and between countries, with general anaesthesia and spinal anaesthesia representing the 2 most common approaches. Limited randomised evidence exists regarding potential short-term or long-term differences in outcomes between patients receiving spinal or general anaesthesia for hip fracture surgery.MethodsThe REGAIN trial (Regional vs General Anesthesia for Promoting Independence after Hip Fracture) is an international, multicentre, pragmatic randomised controlled trial. 1600 previously ambulatory patients aged 50 and older will be randomly allocated to receive either general or spinal anaesthesia for hip fracture surgery. The primary outcome is a composite of death or new inability to walk 10 feet or across a room at 60 days after randomisation, which will be assessed via telephone interview by staff who are blinded to treatment assignment. Secondary outcomes will be assessed by in-person assessment and medical record review for in-hospital end points (delirium; major inpatient medical complications and mortality; acute postoperative pain; patient satisfaction; length of stay) and by telephone interview for 60-day, 180-day and 365-day end points (mortality; disability-free survival; chronic pain; return to the prefracture residence; need for new assistive devices for ambulation; cognitive impairment).Ethics and disseminationThe REGAIN trial has been approved by the ethics boards of all participating sites. Recruitment began in February 2016 and will continue until the end of 2019. Dissemination plans include presentations at scientific conferences, scientific publications, stakeholder engagement efforts and presentation to the public via lay media outlets.Trial registration numberNCT02507505, Pre-results.

Summary Points * Although there is substantial consensus regarding the need for interim monitoring of certain types of trials, there is controversy about specific aspects of data monitoring. * Approaches to ensuring independence of those who perform the interim monitoring and confidentiality of interim data vary substantially by type of trial and trial funder. * The \"independent statistician\" model, involving a separate statistician to analyze interim data and report to the data monitoring committee (DMC), remains controversial but provides important protections of data integrity. * Early stopping guidelines should be clearly understood and accepted by all parties, and only deviated from if there are unexpected findings that confound the overall benefit-risk assessment at interim analysis. * Liability of DMC members is an important concern that has not been dealt with adequately by either commercial or government trial sponsors. [...]concerns about potential exposure of DMC members to litigation are relatively recent but need to be taken seriously by DMC members and trial sponsors.

Background To identify safety signals by manual review of individual report in large surveillance databases is time consuming; such an approach is very unlikely to reveal complex relationships between medications and adverse events. Since the late 1990s, efforts have been made to develop data mining tools to systematically and automatically search for safety signals in surveillance databases. Influenza vaccines present special challenges to safety surveillance because the vaccine changes every year in response to the influenza strains predicted to be prevalent that year. Therefore, it may be expected that reporting rates of adverse events following flu vaccines (number of reports for a specific vaccine-event combination/number of reports for all vaccine-event combinations) may vary substantially across reporting years. Current surveillance methods seldom consider these variations in signal detection, and reports from different years are typically collapsed together to conduct safety analyses. However, merging reports from different years ignores the potential heterogeneity of reporting rates across years and may miss important safety signals. Method Reports of adverse events between years 1990 to 2013 were extracted from the Vaccine Adverse Event Reporting System (VAERS) database and formatted into a three-dimensional data array with types of vaccine, groups of adverse events and reporting time as the three dimensions. We propose a random effects model to test the heterogeneity of reporting rates for a given vaccine-event combination across reporting years. The proposed method provides a rigorous statistical procedure to detect differences of reporting rates among years. We also introduce a new visualization tool to summarize the result of the proposed method when applied to multiple vaccine-adverse event combinations. Result We applied the proposed method to detect safety signals of FLU3, an influenza vaccine containing three flu strains, in the VAERS database. We showed that it had high statistical power to detect the variation in reporting rates across years. The identified vaccine-event combinations with significant different reporting rates over years suggested potential safety issues due to changes in vaccines which require further investigation. Conclusion We developed a statistical model to detect safety signals arising from heterogeneity of reporting rates of a given vaccine-event combinations across reporting years. This method detects variation in reporting rates over years with high power. The temporal trend of reporting rate across years may reveal the impact of vaccine update on occurrence of adverse events and provide evidence for further investigations.

In this subtrial involving middle-aged and older men with hypogonadism, testosterone treatment did not result in a lower incidence of clinical fracture than placebo. Fracture incidence was numerically higher with testosterone.

Randomized clinical trials require a mechanism to safeguard the enrolled patients from harm that could result from participation. This article reviews the role of data monitoring committees in the performance of randomized clinical trials. In the five decades since the completion of the Greenberg Report recommendations in 1967 (which were later published 1 ), independent groups of experts have monitored the progress of many clinical trials for early definitive evidence of benefit, convincing evidence of harm, or sufficient evidence of no potential benefit to render continuation of the trial to be futile. Such monitoring is motivated primarily by an ethical imperative; for trials of treatments intended to prevent or delay serious outcomes, one would want to stop the trial and make the superior treatment available as soon as the evidence was definitive. The assessment of . . .

This randomized trial showed no effect of early adenotonsillectomy, as compared with watchful waiting, on the primary outcome of attention and executive functioning in children with obstructive sleep apnea. Many secondary outcomes favored early surgery. The childhood obstructive sleep apnea syndrome is associated with numerous adverse health outcomes, including cognitive and behavioral deficits. 1 The most commonly identified risk factor for the childhood obstructive sleep apnea syndrome is adenotonsillar hypertrophy. Thus, the primary treatment is adenotonsillectomy, which accounts for more than 500,000 procedures annually in the United States alone. 2 Nevertheless, there has been no controlled study evaluating the benefits and risks of adenotonsillectomy, as compared with watchful waiting, for the management of the obstructive sleep apnea syndrome. The Childhood Adenotonsillectomy Trial (CHAT) was designed to evaluate the efficacy of early adenotonsillectomy versus watchful waiting with supportive . . .