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Abstract Purpose We aim to thoroughly compare past and current methods that leverage baseline covariate information to estimate the average treatment effect (ATE) using data from of randomized clinical trials (RCTs). We especially focus on their performance, efficiency gain, and power. Methods We compared 6 different methods using extensive Monte-Carlo simulation studies: the unadjusted estimator, i.e., analysis of variance (ANOVA), the analysis of covariance (ANCOVA), the analysis of heterogeneous covariance (ANHECOVA), the inverse probability weighting (IPW), the augmented inverse probability weighting (AIPW), and the overlap weighting (OW) as well as the augmented overlap weighting (AOW) estimators. The performance of these methods is assessed using the relative bias (RB), the root mean square error (RMSE), the model-based standard error (SE) estimation, the coverage probability (CP), and the statistical power. Results Even with a well-executed randomization, adjusting for baseline covariates by an appropriate method can be a good practice. When the outcome model(s) used in a covariate-adjusted method is closer to the correctly specified model(s), the efficiency and power gained can be substantial. We also found that most covariate-adjusted methods can suffer from the high-dimensional curse, i.e., when the number of covariates is relatively high compared to the sample size, they can have poor performance (along with lower efficiency) in estimating ATE. Among the different methods we compared, the OW performs the best overall with smaller RMSEs and smaller model-based SEs, which also result in higher power when the true effect is non-zero. Furthermore, the OW is more robust when dealing with the high-dimensional issue. Conclusion To effectively use covariate adjustment methods, understanding their nature is important for practical investigators. Our study shows that outcome model misspecification and high-dimension are two main burdens in a covariate adjustment method to gain higher efficiency and power. When these factors are appropriately considered, e.g., performing some variable selections if the data dimension is high before adjusting covariate, these methods are expected to be useful.

ObjectivesLinking neighborhood- and patient-level data provides valuable information about the influence of upstream social determinants of health (SDOH). However, sharing of these data across health systems presents challenges. We set out to develop a pipeline to acquire, deidentify, and share neighborhood-level SDOH data across multiple health systems.MethodsWe created a pipeline centered around Decentralized Geomarker Assessment for Multi-Site Studies (DeGAUSS) that utilizes containerization to geocode patient addresses and obtain neighborhood-level SDOH variables. We compared DeGAUSS to a third-party vendor geocoding tool available at Duke Health using a cohort of adult patients referred for abdominal transplant from January 1, 2016, to December 31, 2022. We calculated Cohen's Kappa and percent disagreement at census block group and tract levels, and by Area Deprivation Index, urbanicity, and year.ResultsThe pipeline successfully generated SDOH data for 97.8% of addresses. There was high concordance between DeGAUSS and the vendor tool at the census block group (0.93) and tract levels (0.95). At the block group level, disagreement proportion differed by year and urbanicity, with larger disagreement in the rural category than in micropolitan and metropolitan categories (13%, 7%, 6.2%, respectively).Discussion and conclusionWe describe a novel pipeline that can facilitate the secure acquisition and sharing of neighborhood-level SDOH without sharing PHI. The pipeline can be scaled to include additional social, climate, and environmental variables, and can be extended to an unlimited number of health systems.

Background Evidence suggests intracerebral hemorrhage survivors have earlier recovery compared with ischemic stroke survivors. The Centers for Medicare and Medicaid Services prospective payment system instituted documentation rules for inpatient rehabilitation facilities (IRFs) in 2010, with the goal of optimizing patient selection. We investigated whether these requirements limited IRF and increased skilled nursing facility (SNF) use compared with home discharge. Methods and Results Intracerebral hemorrhage discharges to IRF, SNF, or home were estimated using GWTG (Get With The Guidelines) Stroke registry data between January 1, 2008, and December 31, 2015 (n=265 444). Binary hierarchical models determined associations between the 2010 Rule and discharge setting; subgroup analyses evaluated age, geographic region, and hospital type. From January 1, 2008, to December 31, 2009, 45.5% of patients with intracerebral hemorrhage had home discharge, 22.2% went to SNF, and 32.3% went to IRF. After January 1, 2010, there was a 1.06% absolute increase in home discharge, a 0.46% increase in SNF, and a 1.52% decline in IRF. The adjusted odds of IRF versus home discharge decreased 3% after 2010 (adjusted odds ratio [aOR], 0.97; 95% CI, 0.95–1.00). Lower odds of IRF versus home discharge were observed in people aged

Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003–2007, N = 1,869; 3 h, 2009–2016, N = 13,086, and 4.5 h, 2009–2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold.

Background There are conflicting data regarding the benefit of primary prevention implantable cardioverter‐defibrillators (ICDs) in patients with diabetes mellitus and heart failure (HF) with reduced ejection fraction. We aimed to assess the comparative effectiveness of ICD placement in patients with diabetes mellitus and HF with reduced ejection fraction. Methods and Results Data were obtained from the Get With the Guidelines–Health Failure registry, linked with claims from the Centers for Medicare & Medicaid Services. We used a Cox proportional hazards model censored at 5 years with propensity score matching. Of the 17 186 patients with HF with reduced ejection fraction from the Centers for Medicare & Medicaid Services claims database (6540 with diabetes mellitus; 38%), 1677 (646 with diabetes mellitus; 39%) received an ICD during their index HF hospitalization or were prescribed an ICD at discharge. Patients with diabetes mellitus and an ICD (n=646), as compared with those without an ICD (n=1031), were more likely to be younger (74 versus 78 years of age) and have coronary artery disease (68% versus 60%). After propensity matching, ICD use among patients with diabetes mellitus, as compared with those without an ICD, was associated with a reduced risk of all‐cause mortality at 5 years after HF discharge (54% versus 59%; multivariable hazard ratio, 0.73; 95% CI, 0.64–0.82; P

Objectives: The relationship between prior glycemic status and outcomes in intracerebral hemorrhage (ICH) is not established. We hypothesized that higher hemoglobin (Hb) A1c is associated with worse outcomes in ICH. Patients and methods: Using the GWTG-Stroke registry, data on patients with ICH between April 1, 2003 and September 30, 2015 were harvested. Patients were divided into four ordinal groups based on HbA1c values of 8.0%. Outcomes (mortality, modified Rankin Scale (mRS), home discharge and independent ambulatory status) were analyzed for patients overall and separately for patients with or without history of diabetes using multivariable regression models. Results: Among 75,455 patients with ICH (with available HbA1c data), patients with lower HbA1c (8.0%), (15.0%; 205/1364) were associated with higher in-hospital mortality. Lower HbA1c was also associated with higher mRS, less chance of going home, and lower likelihood of having independent ambulatory status in patients with prior history of diabetes. Conclusions: Among patients with no reported history of diabetes, both very low and very high HbA1c were directly associated with higher in-hospital mortality. Only very low HbA1c was associated with higher mortality in known diabetic patients. Further studies are needed to better define the relationship between HbA1c and outcomes, for it may have important implications for care of ICH patients.

Background Patients presenting to hospitals during non–weekday hours experience worse outcomes, often attributed to reduced staffing. The American Heart Association International Stroke Conference (ISC) is well attended by stroke clinicians. We sought to determine whether patients with acute ischemic stroke (AIS) admitted during the ISC receive less guideline‐adherent care and experience worse outcomes. Methods and Results We performed a retrospective cohort study of US hospitals participating in Get With The Guidelines–Stroke and assessed use of intravenous tissue plasminogen activator, other quality measures, and outcomes for patients with AIS admitted during the ISC compared with those admitted the weeks before and after the conference. A total of 69 738 patients with AIS were included: mean age, 72 years; 52% women; 29% nonwhite. There was no difference between the average weekly number of AIS cases admitted during ISC weeks versus non‐ISC weeks (1984 versus 1997; P=0.95). Patient and hospital characteristics were similar between ISC and non‐ISC time periods. There were no significant differences in 14 quality metrics and 5 clinical outcomes between patients with AIS treated during the ISC versus non‐ISC weeks. Patients with AIS who presented within 2 hours of onset had no difference in the likelihood of receiving intravenous tissue plasminogen activator within 3 hours (adjusted odds ratio, 0.89; 95% confidence interval, 0.77–1.03; P=0.13) or the likelihood of receiving intravenous tissue plasminogen activator within 60 minutes of arrival (adjusted odds ratio, 0.92; 95% confidence interval, 0.83–1.02; P=0.13). Conclusions Patients with acute stroke admitted to Get With The Guidelines–Stroke hospitals during ISC received the same quality care and had similar outcomes as patients admitted at other times.

Objective This study reports on food insecurity (FI) amidst the COVID-19 pandemic. Participants and methods College students in four regions of the US completed the two-item validated Hunger Vital Sign™ screening tool on Qualtrics. Results FI increased significantly after March 2020 among US students (worry about food running out: 25% to 35%; food did not last: 17% to 21%) with significant regional increase in the Midwest and South. An adjusted multivariable logistic regression model indicated students that ran out of food were significantly at greater odds of experiencing hardship with paying bills (AOR: 5.59, 95% CI =3.90-8.06). Conclusions The findings identified an increase in the prevalence of FI among college students during the pandemic. Suggestions of how to address FI are discussed.

BackgroundGuidelines recommend continuation or initiation of guideline‐directed medical therapy, including angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers (ACEi/ARB), in hospitalized patients with heart failure with reduced ejection fraction. Methods and ResultsUsing the Get With The Guidelines‐Heart Failure Registry, we linked clinical data from 16 052 heart failure with reduced ejection fraction (ejection fraction ≤40%) patients with Medicare claims data. We divided ACEi/ARB‐eligible patients into 4 categories based on admission and discharge ACEi/ARB use: continued (reference group), started, discontinued, or not started on therapy. A multivariable Cox proportional hazard model was used to determine the association between ACEi/ARB category and outcomes. Most, 90.5%, were discharged on ACEi/ARB (59.6% continued and 30.9% newly started). Of those discharged without ACEi/ARB, 1.9% were discontinued, and 7.5% were eligible but not started. Thirty‐day mortality was 3.5% for patients continued and 4.1% for patients started on ACEi/ARB. In contrast, 30‐day mortality was 8.8% for patients discontinued (adjusted hazard ratio [HRadj] 1.92; 95% CI 1.32‐2.81; P