Hepatitis B virus infection in HIV-positive individuals in the UK collaborative HIV cohort (UK CHIC) study.

Hepatitis B virus (HBV) infection is an increasingly important cause of morbidity and mortality in HIV-infected adults. This study aimed to determine the prevalence and incidence of HBV in the UK CHIC Study, a multicentre observational cohort

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Implicit and explicit anti-fat bias among a large sample of medical doctors by BMI, race/ethnicity and gender.

Overweight patients report weight discrimination in health care settings and subsequent avoidance of routine preventive health care. The purpose of this study was to examine implicit and explicit attitudes about weight among a large group of medical doctors (MDs) to determine the pervasiveness of negative attitudes about weight among MDs. Test-takers voluntarily accessed a public Web site, known as Project Implicit®, and opted to complete the Weight Implicit Association Test (IAT) (N = 359,261). A sub-sample identified their highest level of education as MD (N = 2,284). Among the MDs, 55% were female, 78% reported their race as white, and 62% had a normal range BMI. This large sample of test-takers showed strong implicit anti-fat bias (Cohen's d = 1.0). MDs, on average, also showed strong implicit anti-fat bias (Cohen's d = 0.93). All test-takers and the MD sub-sample reported a strong preference for thin people rather than fat people or a strong explicit anti-fat bias. We conclude that strong implicit and explicit anti-fat bias is as pervasive among MDs as it is among the general public. An important area for future research is to investigate the association between providers' implicit and explicit attitudes about weight, patient reports of weight discrimination in health care, and quality of care delivered to overweight patients

Characteristics of Weight IAT Test-taker Sample.

<p>BMI: Calculated using the CDC Formula: weight (lb)/[height (in)] 2×703.</p

Pairwise Comparisons of Implicit and Explicit Weight Attitudes for All Test Takers and MDs (medical doctors) as a function of Gender, and for MDs as a function of BMI and Race/Ethnicity categories.

*<p>Adjustment for multiple comparisons: Bonferroni.</p><p>(a) Mean Difference.</p><p>(b) medical doctor.</p

Inter-correlation Between Implicit and Explicit Weight Attitude Measures.

<p>a. N represents total test takers for whom we have both implicit and explicit measures.</p><p>b. Pearson’s correlation <i>(r).</i></p

Implicit and Explicit Weight Attitude Measures for MDs (medical doctors) by Race and Ethnicity Category.

<p>a. ηp² is the effect magnitude in a univariate regression with race/ethnicity as the single predictor.</p><p>b. Implicit and explicit measures range from −2 to +2, with zero indicating no bias.</p><p>c. A positive mean indicates some degree of preference for “Thin” persons, a negative mean indicates some degree of preference for “Fat” persons.</p><p>d. Cohen’s <i>d</i> is a standardized effect size, comparing the means to M = 0 (no bias), interpreted as; <i>d</i> of 0.2 = small effect, <i>d</i> of 0.5 = medium effect, and <i>d</i> ≥0.8 = large effect.</p