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Background: High-quality research in cardiovascular prevention, as in other fields, requires inclusion of a broad range of data sets from different sources. Integrating and harmonizing different data sources are essential to increase generalizability, sample size, and representation of understudied populations-strengthening the evidence for the scientific questions being addressed., Methods: Here, we describe an effort to build an open-access repository and interactive online portal for researchers to access the metadata and code harmonizing data from 4 well-known cohort studies-the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study, FHS (Framingham Heart Study), MESA (Multi-Ethnic Study of Atherosclerosis), and ARIC (Atherosclerosis Risk in Communities) study. We introduce a methodology and a framework used for preprocessing and harmonizing variables from multiple studies., Results: We provide a real-case study and step-by-step guidance to demonstrate the practical utility of our repository and interactive web page. In addition to our successful development of such an open-access repository and interactive web page, this exercise in harmonizing data from multiple cohort studies has revealed several key themes. These themes include the importance of careful preprocessing and harmonization of variables, the value of creating an open-access repository to facilitate collaboration and reproducibility, and the potential for using harmonized data to address important scientific questions and disparities in cardiovascular disease research., Conclusions: By integrating and harmonizing these large-scale cohort studies, such a repository may improve the statistical power and representation of understudied cohorts, enabling development and validation of risk prediction models, identification and investigation of risk factors, and creating a platform for racial disparities research., Registration: URL: https://precision.heart.org/duke-ninds., Competing Interests: Disclosures Drs Hall, Mallya, Zhao, and V. Manchanda are employees of the American Heart Association (AHA). The other authors report no conflicts.

Importance: Randomized clinical trials (RCTs) are critical in advancing patient care, yet conducting such large-scale trials requires tremendous resources and coordination. Clinical site start-up performance metrics can provide insight into opportunities for improved trial efficiency but have not been well described., Objective: To measure the start-up time needed to reach prespecified milestones across sites in large cardiovascular RCTs in North America and to evaluate how these metrics vary by time and type of regulatory review process., Design, Setting, and Participants: This cohort study evaluated cardiovascular RCTs conducted from July 13, 2004, to February 1, 2017. The RCTs were coordinated by a single academic research organization, the Duke Clinical Research Institute. Nine consecutive trials with completed enrollment and publication of results in their target journal were studied. Data were analyzed from December 4, 2019, to January 11, 2021., Exposures: Year of trial enrollment initiation (2004-2007 vs 2008-2012) and use of a central vs local institutional review board (IRB)., Main Outcomes and Measures: The primary outcome was the median start-up time (from study protocol delivery to first participant enrollment) as compared by trial year and type of IRB used. The median start-up time for the top 10% of sites was also reported. Secondary outcomes included time to site regulatory approval, time to contract execution, and time to site activation., Results: For the 9 RCTs included, the median site start-up time shortened only slightly over time from 267 days (interquartile range [IQR], 185-358 days) for 2004-2007 trials to 237 days (IQR, 162-343 days) for 2008-2012 trials (overall median, 255 days [IQR, 177-350 days]; P < .001). For the top 10% of sites, median start-up time was 107 days (IQR, 95-121 days) for 2004-2007 trials vs 104 days (IQR, 84-118 days) for 2008-2012 trials (overall median, 106 days [IQR, 90-120 days]; P = .04). The median start-up time was shorter among sites using a central IRB (199 days [IQR, 140-292 days]) than those using a local IRB (287 days [IQR, 205-390 days]; P < .001)., Conclusions and Relevance: This cohort study of North American research sites in large cardiovascular RCTs found a duration of nearly 9 months from the time of study protocol delivery to the first participant enrollment; this metric was only slightly shortened during the study period but was reduced to less than 4 months for top-performing sites. These findings suggest that the use of central IRBs has the potential to improve RCT efficiency.

Objective: To identify the prevalence, treatment, and low-density lipoprotein cholesterol (LDL-C) control of individuals with LDL-C ≥190 ​mg/dL in contemporary clinical practice., Methods: We included adults (age ≥18 years) with LDL-C ≥190 ​mg/dL, at least one LDL-C level drawn from 255 health systems participating in Cerner HealthFacts database (2000-2017, n ​= ​4,623,851), and a detailed examination within Duke University Health System (DUHS, 2015-2017, n ​= ​267,710). Factors associated with LDL-C control were evaluated using multivariable logistic regression modeling., Results: The cross-sectional prevalence of LDL-C ≥190 ​mg/dL was 3.0% in Cerner (n ​= ​139,539/4,623,851) and 2.9% at DUHS (n ​= ​7728/267,710); among these, rates of repeat LDL-C measurement within 13 months were low: 27.9% (n ​= ​38,960) in Cerner, 54.5% (n ​= ​4211) at DUHS. Of patients with follow-up LDL-C levels, 23.6% in Cerner had a 50% of greater reduction in LDL-C, 18.3% achieved an LDL-C <100 ​mg/dL and 2.7% ​< ​70 ​mg/dL. At DUHS, 28.4% had a 50% or greater reduction in LDL-C, 28.4% achieved an LDL-C ≤100 ​mg/dL and 4.4% achieved <70 ​mg/dL. Within DUHS, 71.6% with LDL-C ≥190 ​mg/dL were on any statin during follow-up, but only 28.5% were on a high-intensity statin. In multivariable modeling, seeing a cardiologist (Cerner odds ratio [OR] 1.56, confidence interval [CI] 1.33-1.83; DUHS OR 1.89, 95% CI 1.18-3.01) and having diabetes (Cerner OR 1.34 CI 1.23-1.46; DUHS OR 2.07, CI 1.62-2.65) increased odds of LDL-C control, defined as a ≥50% reduction in LDL-C (at Cerner) or initiation of high intensity statin (at DUHS). Prior atherosclerotic cardiovascular disease (OR 1.19, CI 1.07-1.33), hypertension (OR 1.10, CI 1.03-1.18), African American race (OR 0.79, CI 0.71-0.89), and government (vs. private) insurance (OR 0.90, CI 0.83-0.98) were associated with LDL-C control at Cerner. Female sex was associated with lower odds of appropriate therapy (OR 0.69, CI 0.59-0.81) at DUHS., Conclusions: Approximately 3% of United States adults have LDL-C ≥190 ​mg/dL. Among those with very high LDL-C, rates of repeat measurement within one year were low; of those retested, only about one-fourth met guideline-recommended LDL-C treatment goals., (© 2020 The Author(s).)

Background: Comorbid diabetes and substance use diagnoses (SUD) represent a hazardous combination, both in terms of healthcare cost and morbidity. To date, there is limited information about the association of SUD and related mental disorders with type 2 diabetes mellitus (T2DM)., Methods: We examined the associations between T2DM and multiple psychiatric diagnosis categories, with a focus on SUD and related psychiatric comorbidities among adults with T2DM. We analyzed electronic health record (EHR) data on 170,853 unique adults aged ≥18 years from the EHR warehouse of a large academic healthcare system. Logistic regression analyses were conducted to estimate the strength of an association for comorbidities., Results: Overall, 9% of adults (n=16,243) had T2DM. Blacks, Hispanics, Asians, and Native Americans had greater odds of having T2DM than whites. All 10 psychiatric diagnosis categories were more prevalent among adults with T2DM than among those without T2DM. Prevalent diagnoses among adults with T2MD were mood (21.22%), SUD (17.02%: tobacco 13.25%, alcohol 4.00%, drugs 4.22%), and anxiety diagnoses (13.98%). Among adults with T2DM, SUD was positively associated with mood, anxiety, personality, somatic, and schizophrenia diagnoses., Conclusions: We examined a large diverse sample of individuals and found clinical evidence of SUD and psychiatric comorbidities among adults with T2DM. These results highlight the need to identify feasible collaborative care models for adults with T2DM and SUD related psychiatric comorbidities, particularly in primary care settings, that will improve behavioral health and reduce health risk., (Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)