Importance Little is known about how new and expensive drugs diffuse into practice affects health care costs. Objective To describe the variation in second-generation diabetes drug use among Medicare enrollees between 2007 and 2015. AUY-922 cost Design, setting, and participants This population-based, cross-sectional study included data from 100% of Medicare Parts A, B, and D enrollees who first received diabetes drug therapy from January 1, 2007, to December 31, 2015. Patients with type 1 diabetes were excluded. Data were analyzed beginning in the spring of 2018, and revisions were completed in 2019. Exposures For each patient, the initial diabetes drug choice was determined; drugs were classified as first generation (ie, approved before 2000) or second generation (ie, approved after 2000, including dipeptidyl peptidase 4 [DPP-4] inhibitors, glucagon-like peptide-1 [GLP-1] receptor agonists, and sodium-glucose cotransporter-2 [SGLT-2] inhibitors). Main outcomes and measures The primary outcome was the between-practice va, were used at least once by 1716 practices (4.0%) and used in 10% of eligible patients by 872 practices (2.0%) by December 2015. According to Poisson random-effect regression models, beneficiaries in high-prescribing practices were more than 3-fold more likely to receive DPP-4 inhibitors (relative risk, 3.55 [95% CI, 3.42-3.68]), 24-fold more likely to receive GLP-1 receptor agonists (relative risk, 24.06 [95% CI, 14.14-40.94]) and 60-fold more likely to receive SGLT-2 inhibitors (relative risk, 60.41 [95% CI, 15.99-228.22]) compared with beneficiaries in low-prescribing practices. Conclusions and relevance These findings suggest that there was substantial between-practice variation in the use of second-generation diabetes drugs between 2007 and 2015, with a concentration of use among a few prescribers and practices responsible for much of the early diffusion.Importance Single self-reported measures of sleep duration are associated with adverse health outcomes; however, long-term patterns of self-reported sleep duration and their association with cardiovascular events (CVEs) and all-cause mortality remain unknown. Objective To determine whether trajectories of long-term vs single-measure sleep duration are associated with subsequent risk of CVEs and all-cause mortality. Design, setting, and participants The Kailuan study is a prospective, population-based cohort study that began in 2006. The present cohort included 52 599 Chinese adults without atrial fibrillation, myocardial infarction, stroke, or cancer to 2010. Trajectories in sleep duration from January 1, 2006, to December 31, 2010, were identified to investigate the association with risk of CVEs and all-cause mortality from January 1, 2010, to December 31, 2017. Data analysis was conducted from July 1 to October 31, 2019. Exposures Habitual self-reported nocturnal sleep durations were collected in 2006, 2008stable pattern and adjusting for potential confounders, a low-increasing pattern was associated with increased risk of first CVEs (hazard ratio [HR], 1.22; 95% CI, 1.04-1.43), a normal-decreasing pattern was associated with increased risk of all-cause mortality (HR, 1.34; 95% CI, 1.15-1.57), and the low-stable pattern was associated with the highest risk of CVEs (HR, 1.47; 95% CI, 1.05-2.05) and death (HR, 1.50; 95% CI, 1.07-2.10). Conclusions and relevance In this study, sleep duration trajectories with lower or unstable patterns were significantly associated with increased risk of subsequent first CVEs and all-cause mortality. Longitudinal sleep duration patterns may assist in more precise identification of different at-risk groups for possible intervention. People reporting consistently sleeping less than 5 hours per night should be regarded as a population at higher risk for CVE and mortality.Background We previously reported that lymphocytopenia and T cell exhaustion is notable in acute COVID19 patients, especially in aged and severe cases. Thymosin alpha 1 (Tα1) had been used in the treatment of viral infections as an immune response modifier for many years. However, clinical benefits and mechanism of Tα1 supplement to COVID-19 are still unclear. Methods We retrospectively reviewed the clinical outcomes of 76 severe cases with COVID-19 admitted into two hospitals in Wuhan from December 2019 to March 2020. The thymus output in peripheral blood mononuclear cells (PBMCs) from COVID-19 patients was measured by T cell receptor excision circles (TREC). The levels of T cell exhaustion markers PD-1 and Tim-3 on CD8+ T cells were detected by flow cytometry. Results Compared with untreated group, Tα1 treatment significantly reduces mortality of severe COVID-19 patients (11.11% vs. 30.00%, p=0.044). Tα1 timely enhances blood T cell numbers in COVID-19 patients with severe lymphocytopenia (the counts of CD8+ T cells or CD4+ T cells in circulation lower than 400/μL or 650/μL, respectively). Under such conditions, Tα1 also successfully restores CD8+ and CD4+ T cell numbers in aged patients. Meanwhile, Tα1 reduces PD-1 and Tim-3 expression on CD8+ T cells from severe COVID-19 patients in comparison with untreated cases. It is of note that restoration of lymphocytopenia and acute exhaustion of T cells are roughly parallel to the rise of TRECs. Conclusions Tα1 supplement significantly reduce mortality of severe COVID-19 patients. COVID-19 patients with the counts of CD8+ T cells or CD4+ T cells in circulation lower than 400/μL or 650/μL, respectively, gain more benefits from Tα1. Tα1 reverses T cell exhaustion and recovers immune reconstitution through promoting thymus output during SARS-CoV-2 infection.Background Renin-angiotensin-aldosterone system (RAAS) inhibitors may facilitate host cell entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or attenuate organ injury via RAAS blockade. We aimed to assess the associations between prior use of RAAS inhibitors and clinical outcomes among Korean patients with coronavirus 2019 (COVID-19). Methods We performed a nationwide population-based cohort study using the Korean Health Insurance Review and Assessment database. Claim records were screened for 66793 individuals who were tested for COVID-19 until April 8, 2020. Adjusted odds ratios (ORs) were used to compare the clinical outcomes between RAAS inhibitor users and nonusers. Results Among 5179 confirmed COVID-19 cases, 762 patients were RAAS inhibitor users and 4417 patients were nonusers. Relative to nonusers, RAAS inhibitor users were more likely to be older, male, and have comorbidities. Among 1954 hospitalized patients with COVID-19, 377 patients were RAAS inhibitor users and 1577 patients were nonusers.