Background The comparative effectiveness of sulfonylureas and metformin on cardiovascular disease (CVD) outcomes in type 2 diabetes are not well characterized. Objective To compare the effectiveness of sulfonylureas and metformin on the outcome of CVD (acute myocardial infarction, stroke) or death Design Retrospective cohort study Setting National Veterans Health Administration (VHA) databases linked to Medicare files Patients Veterans who initiated metformin or sulfonylureas for diabetes. Patients with chronic kidney disease or serious medical illness were excluded. Measurements Composite outcome of hospitalizations for acute myocardial infarction, stroke, or death. Cox regression analyses compared the incidence of the composite outcome between groups, adjusting for baseline demographics, medications, cholesterol, glycated hemoglobin, creatinine, blood pressure, body mass index, healthcare utilization and co-morbidities. Results Among 253,690 patients (98,665 sulfonylurea and 155,025 metformin initiators) the crude outcome rates were 18.2 and 10.4 per 1000 person-years in sulfonylurea and metformin users, respectively (adjusted hazard ratio [aHR] 1.21, 95% Confidence Intervals [CI] 1.13, 1.30). Results were consistent for both glyburide (aHR 1.26, 95% CI 1.16, 1.37) and glipizide (aHR 1.15, 95% CI 1.06, 1.26) as well as for those with prior history of CVD (aHR 1.25, 95% CI 1.13, 1.55) and without history of CVD (aHR: 1.16, 95% CI: 1.06, 1.29). Results were also consistent in a propensity score-matched analysis. For patients initiating sulfonylureas rather than metformin, we estimated an excess of 1 and 4 CVD events per 1000 person-years for those without and with a CVD history, respectively. Limitations Data on women and minorities is limited but reflective of the VHA population. Conclusions Use of sulfonylureas compared to metformin for initial treatment of diabetes was associated with an increased hazard of CVD events or death.

Objective To evaluate whether early initiation of prophylactic anticoagulation compared with no anticoagulation was associated with decreased risk of death among patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United States. Design Observational cohort study. Setting Nationwide cohort of patients receiving care in the Department of Veterans Affairs, a large integrated national healthcare system. Participants All 4297 patients admitted to hospital from 1 March to 31 July 2020 with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and without a history of anticoagulation. Main outcome measures The main outcome was 30 day mortality. Secondary outcomes were inpatient mortality, initiating therapeutic anticoagulation (a proxy for clinical deterioration, including thromboembolic events), and bleeding that required transfusion. Results Of 4297 patients admitted to hospital with covid-19, 3627 (84.4%) received prophylactic anticoagulation within 24 hours of admission. More than 99% (n=3600) of treated patients received subcutaneous heparin or enoxaparin. 622 deaths occurred within 30 days of hospital admission, 513 among those who received prophylactic anticoagulation. Most deaths (510/622, 82%) occurred during hospital stay. Using inverse probability of treatment weighted analyses, the cumulative incidence of mortality at 30 days was 14.3% (95% confidence interval 13.1% to 15.5%) among those who received prophylactic anticoagulation and 18.7% (15.1% to 22.9%) among those who did not. Compared with patients who did not receive prophylactic anticoagulation, those who did had a 27% decreased risk for 30 day mortality (hazard ratio 0.73, 95% confidence interval 0.66 to 0.81). Similar associations were found for inpatient mortality and initiation of therapeutic anticoagulation. Receipt of prophylactic anticoagulation was not associated with increased risk of bleeding that required transfusion (hazard ratio 0.87, 0.71 to 1.05). Quantitative bias analysis showed that results were robust to unmeasured confounding (e-value lower 95% confidence interval 1.77 for 30 day mortality). Results persisted in several sensitivity analyses. Conclusions Early initiation of prophylactic anticoagulation compared with no anticoagulation among patients admitted to hospital with covid-19 was associated with a decreased risk of 30 day mortality and no increased risk of serious bleeding events. These findings provide strong real world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial treatment for patients with covid-19 on hospital admission.

A multifactorial intervention including patient education improved blood pressure control compared with provider education alone.

Although blocking or pairing before randomization is a basic principle of experimental design, the principle is almost invariably applied to at most one or two blocking variables. Here, we discuss the use of optimal multivariate matching prior to randomization to improve covariate balance for many variables at the same time, presenting an algorithm and a case-study of its performance. The method is useful when all subjects, or large groups of subjects, are randomized at the same time. Optimal matching divides a single group of 2n subjects into n pairs to minimize covariate differences within pairs-the so-called nonbipartite matching problem-then one subject in each pair is picked at random for treatment, the other being assigned to control. Using the baseline covariate data for 132 patients from an actual, unmatched, randomized experiment, we construct 66 pairs matching for 14 covariates. We then create 10000 unmatched and 10000 matched randomized experiments by repeatedly randomizing the 132 patients, and compare the covariate balance with and without matching. By every measure, every one of the 14 covariates was substantially better balanced when randomization was performed within matched pairs. Even after covariance adjustment for chance imbalances in the 14 covariates, matched randomizations provided more accurate estimates than unmatched randomizations, the increase in accuracy being equivalent to, on average, a 7% increase in sample size. In randomization tests of no treatment effect, matched randomizations using the signed rank test had substantially higher power than unmatched randomizations using the rank sum test, even when only 2 of 14 covariates were relevant to a simulated response. Unmatched randomizations experienced rare disasters which were consistently avoided by matched randomizations.

The time course of cardiovascular disease (CVD) risk after smoking cessation is unclear. Risk calculators consider former smokers to be at risk for only 5 years. OBJECTIVE To evaluate the association between years since quitting smoking and incident CVD. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of prospectively collected data from Framingham Heart Study participants without baseline CVD (original cohort: attending their fourth examination in 1954-1958; offspring cohort: attending their first examination in 1971-1975) who were followed up through December 2015. EXPOSURES Time-updated self-reported smoking status, years since quitting, and cumulative pack-years. MAIN OUTCOMES AND MEASURES Incident CVD (myocardial infarction, stroke, heart failure, or cardiovascular death). Primary analyses included both cohorts (pooled) and were restricted to heavy ever smokers (Ն20 pack-years). RESULTS The study population included 8770 individuals (original cohort: n = 3805; offspring cohort: n = 4965) with a mean age of 42.2 (SD, 11.8) years and 45% male. There were 5308 ever smokers with a median 17.2 (interquartile range, 7-30) baseline pack-years, including 2371 heavy ever smokers (406 [17%] former and 1965 [83%] current). Over 26.4 median follow-up years, 2435 first CVD events occurred (original cohort: n = 1612 [n = 665 among heavy smokers]; offspring cohort: n = 823 [n = 430 among heavy smokers]). In the pooled cohort, compared with current smoking, quitting within 5 years was associated with significantly lower rates of incident CVD (incidence rates per 1000 person-years: current smoking, 11.56 [95% CI, 10.30-12.98]; quitting within 5 years, 6.94 [95% CI, 5.61-8.59]; difference, −4.51 [95% CI, −5.90 to −2.77]) and lower risk of incident CVD (hazard ratio, 0.61; 95% CI, 0.49-0.76). Compared with never smoking, quitting smoking ceased to be significantly associated with greater CVD risk between 10 and 15 years after cessation in the pooled cohort (incidence rates per 1000 person-years: never smoking, 5.09 [95% CI, 4.52-5.74]; quitting within 10 to <15 years, 6.31 [95% CI, 4.93-8.09]; difference, 1.27 [95% CI, −0.10 to 3.05]; hazard ratio, 1.25 [95% CI, 0.98-1.60]). CONCLUSIONS AND RELEVANCE Among heavy smokers, smoking cessation was associated with significantly lower risk of CVD within 5 years relative to current smokers. However, relative to never smokers, former smokers' CVD risk remained significantly elevated beyond 5 years after smoking cessation.

Importance Preferred second line medication for diabetes treatment after metformin failure remains uncertain. Objective We compared time to acute myocardial infarction [AMI], stroke, or death in a cohort of metformin initiators who added insulin or a sulfonylurea. Design Retrospective cohort constructed using national Veterans Health Administration, Medicare, and National Death Index databases. Participants Veterans initially treated with metformin from 2001 through 2008 who subsequently added either insulin or sulfonylurea. Each insulin intensifier was propensity score matched by characteristics to five sulfonylurea intensifiers. Patients were followed through September, 2011 for primary analyses or September, 2009 for cause of death analyses. Main Outcome Measures Risk of a composite outcome of AMI, stroke hospitalization or all-cause death was compared between therapies using marginal structural Cox proportional hazard models to adjust for baseline and time-varying demographics, medications, cholesterol, hemoglobin A1c, creatinine, blood pressure, body mass index, and co-morbidities. Results Among 178,341 metformin monotherapy patients, 2,948 and 39,990 added insulin or sulfonylurea, respectively. Propensity score matching yielded 2,436 metformin+insulin and 12,180 metformin+sulfonylurea patients. At intensification, the median (interquartile range) time on metformin was 14 months (5, 30) and HbA1c was 8.1% (7.2, 9.9). There were 172 versus 634 events for the primary outcome among those who added insulin versus sulfonylureas respectively (42 versus 33 events per 1000 person-years, adjusted hazard ratio [aHR] 1.30, 95% confidence interval [CI] 1.07, 1.58, p=0.009). AMI and stroke rates were statistically similar 41 versus 229 (10.2 and 11.9 per 1000 person years, aHR 0.88,95% CI 0.59, 1.30, p=0.52), while all-cause death rates were137 versus 444, respectively (33.7 and 22.7 per 1000 person-years, aHR 1.44, 95% CI,1.15, 1.79, p=0.001). There were 54 versus 258 secondary outcomes: AMI, stroke hospitalizations or cardiovascular deaths (22.8 vs. 22.5 events per 1000 person years aHR 0.98, 95% CI 0.71, 1.34. p=0.87). Conclusions Among patients with diabetes using metformin, the addition of insulin versus sulfonylurea was associated with an increased risk of a composite of nonfatal cardiovascular outcomes and all-cause mortality. These findings require further investigation to understand risks associated with insulin use in these patients.

Matching is a powerful statistical tool in design and analysis. Conventional two-group, or bipartite, matching has been widely used in practice. However, its utility is limited to simpler designs. In contrast, nonbipartite matching is not limited to the two-group case, handling multiparty matching situations. It can be used to find the set of matches that minimize the sum of distances based on a given distance matrix. It brings greater flexibility to the matching design, such as multigroup comparisons. Thanks to improvements in computing power and freely available algorithms to solve nonbipartite problems, the cost in terms of computation time and complexity is low. This article reviews the optimal nonbipartite matching algorithm and its statistical applications, including observational studies with complex designs and an exact distribution-free test comparing two multivariate distributions. We also introduce an R package that performs optimal nonbipartite matching. We present an easily accessible web application to make nonbipartite matching freely available to general researchers.

The CPOE-based intravenous insulin protocol improved glycemia control in SICU patients compared to a previous manual protocol, and reduced time to insulin therapy initiation. Integrating a computer-based insulin protocol into a CPOE system achieved efficient, safe, and effective glycemia control in SICU patients.