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Importance Medicaid expansion was widely expected to alleviate the financial stresses faced by hospitals by providing additional revenue in the form of Medicaid reimbursements from patients previously receiving uncompensated care. Among nonprofit hospitals, which receive tax-exempt status in part because of their provision of uncompensated care, Medicaid expansion could have released hospital funds toward other community benefit activities. Objective To examine changes in nonprofit hospital spending on community benefit activities after Medicaid expansion. Design, setting, and participants This cohort study used difference-in-differences analysis of 1666 US nonprofit hospitals that filed Internal Revenue Service Form 990 Schedule H detailing their community benefit expenditures between 2011 and 2017. The analysis was conducted from February to September 2019. Exposures State Medicaid expansion between 2011 and 2017. Main outcomes and measures Percentage of hospital operating expenditures attributable to chariverall (-0.24 [95% CI, -0.48 to 0.00] percentage points; P = .049). Direct community expenditures remained more stable in small hospitals (-0.07 [95% CI, -0.20 to 0.05] percentage points; P =.26) compared with large hospitals (-0.37 [95% CI, -0.86 to 0.12] percentage points; P = .14) and in nonurban hospitals (0.02 [95% CI, -0.09 to 0.14] percentage points; P = .70) compared with urban hospitals (-0.36 [95% CI, -0.73 to 0.01] percentage points; P = .06). Conclusions and relevance In this study, Medicaid expansion was associated with a decrease in nonprofit hospitals' burden of providing uncompensated care, but this financial relief was not redirected toward spending on other community benefits.This case series reports a systematic assessment of deep vein thrombosis among patients in an intensive care unit in France with severe coronavirus disease 2019 (COVID-19).Background Delays in early infant diagnosis and antiretroviral treatment (ART) initiation in developing countries frequently result in malnutrition at initial presentation with associated higher mortality and delayed immune recovery. The optimal timing of ART initiation is yet to be established. Methods Eighty-two children admitted with HIV and severe acute malnutrition (SAM) between July 2012 and December 2015 were enrolled. Patients were randomized to initiate ART within 14 days from admission (early arm) or delay ART initiation until nutritional recovery and >14 days after admission (delayed arm). All patients received a standardized treatment and feeding protocol and were followed to 48 weeks. Results The mean age of the patients at baseline was 23.3 months (standard deviation [SD], 27.9; range, 1.6-129 months). The mean time from admission to ART initiation was 5.6 days (SD, 4.4) in the early arm and 23 days (SD, 5.8) in the delayed arm (P less then .001). There was no significant difference in mortality (P = .62), virologic response (P = .53), and anthropometric response (P = .57) between the 2 groups at 48 weeks. However, the rates of change in CD4, viral load, weight for age z score, and height for age z score occurred earlier and favored the delayed arm at early time points but were not significant at 24 and 48 months. Conclusions Despite initial improved responses in the delayed arm, lack of difference in outcome at 48 weeks supports a pragmatic approach with earlier ART initiation in children living with HIV admitted with SAM.In this randomised controlled study of ART initiation in children admitted with HIV and severe acute malnutrition (SAM), despite initial improved responses in the delayed arm, lack of difference in outcome at 48 weeks supports a pragmatic approach with earlier ART initiation in children living with HIV admitted with SAM. Clinical trials registration PACTR 21609001751384.Importance In response to the opioid epidemic, policies aiming to reduce opioid prescribing, misuse, and abuse may have the unintended consequence of restricting access to necessary opioid therapy for cancer-related pain. It is unknown how opioid prescribing patterns have changed among generalists and oncologists during this era. Objective To examine trends in opioid prescription rates for Medicare Part D beneficiaries from 2013 to 2017 among oncologists and generalists. Design, setting, and participants This repeated cross-sectional study of generalist physicians (internal medicine, family medicine, geriatric medicine, general practice) and oncology specialists (medical oncology, hematology-oncology, and radiation oncology) analyzed the Medicare Provider Utilization and Payment Data Part D prescriber files from 2013 to 2017. Exposures Generalist vs oncology specialty. Pyridostatin Main outcomes and measures Outcomes included physician-level rates of both opioid and long-acting opioid prescriptions per 100 Medicare Part Dthe extent of opioid prescribing in the Medicare population. Similar declines between generalists and oncologists raise concern that access to cancer pain management may have been inadvertently restricted. How much of the decrease in prescribing by oncologists is appropriate vs inappropriate deserves further investigation.Introduction UK countries implemented smoke-free public places legislation and increased the legal age for tobacco purchase from 16-18 years between 2006 and 2008. We evaluated the immediate and long-term impacts of these UK policy changes on youth smoking uptake, and inequalities therein. Methods We studied 74,960 person-years of longitudinal data from 14,992 youth (aged 11-15 years) in annual UK household surveys between 1994 and 2016. Discrete-time event history analyses examined whether changes in rates of youth smoking transitions (initiation, experimentation, and escalation to daily smoking or quitting) or their inequalities (by parental education) were associated with policy implementation. Parallel analyses examined smoke-free legislation and the change in legal age. We interpret the results as combined effect of the two pieces of legislation as their implementation dates were too close to identify separate effects. Models were adjusted for sex, age, UK country, historical year, tobacco taxation, and e-cigarette prevalence, with multiple imputation for missing data.