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Importance: Commonly used risk assessment tools for cardiovascular disease might not be accurate for HIV-infected patients. Objective: We aimed to develop a model to accurately predict the 10-year cardiovascular disease (CV) risk of HIV-infected patients. Design: In this retrospective cohort study, adult HIV-infected patients seen at Boston Medical Center between March 2012 and January 2017 were divided into model development and validation cohorts. Setting: Boston Medical Center, a tertiary, academic medical center. Participants: Adult HIV-infected patients, seen in inpatient and outpatient setting. Main Outcomes and Measures: We used logistic regression to create a prediction risk model for cardiovascular events using data from the development cohort. Using a point-based risk-scoring system, we summarized the relationship between risk factors and cardiovascular disease (CVD) risk. We then used the area under the receiver operating characteristics curve (AUC) to evaluate model discrimination. Finally, we tested the model using a validation cohort. Results: 1914 individuals met the inclusion criteria. The model had excellent discrimination for CVD risk [AUC 0.989; (95% CI: 0.986–0.993)] and included the following 11 variables: male sex (95% CI: 2.53–3.99), African American race/ethnicity (95% CI: 1.50–3.13), current age (95% CI: 0.07–0.13), age at HIV diagnosis (95% CI: −0.10–(−0.02)), peak HIV viral load (95% CI: 9.89 × 10−7–3.00 × 10−6), nadir CD4 lymphocyte count (95% CI: −0.03–(−0.02)), hypertension (95% CI: 0.20–1.54), hyperlipidemia (95% CI: 3.03–4.60), diabetes (95% CI: 0.61–1.89), chronic kidney disease (95% CI: 1.26–2.62), and smoking (95% CI: 0.12–2.39). The eleven-parameter multiple logistic regression model had excellent discrimination [AUC 0.957; (95% CI: 0.938–0.975)] when applied to the validation cohort. Conclusions and Relevance: Our novel HIV-CARDIO-PREDICT Score may provide a rapid and accurate evaluation of CV disease risk among HIV-infected patients and inform prevention measures.

Abstract Objective To determine whether vascular risk factor burden in mid‐ or late‐life associates with postmortem vascular and neurodegenerative pathologies in a community‐based sample. Methods We studied participants from the Framingham Heart Study who participated in our voluntary brain bank program. Overall vascular risk factor burden was calculated using the Framingham Stroke Risk Profile (FSRP). Mid‐life FSRP was measured at 50 to 60 years of age. Following death, brains were autopsied and semi‐quantitatively assessed by board‐certified neuropathologists for cerebrovascular outcomes (cortical infarcts, subcortical infarcts, atherosclerosis, arteriosclerosis) and Alzheimer’s disease pathology (Braak stage, cerebral amyloid angiopathy, and neuritic plaque score). We estimated adjusted odds ratios between vascular risk burden (at mid‐life and before death) and neuropathological outcomes using logistic and proportional‐odds logistic models. Results The median time interval between FSRP and death was 33.4 years for mid‐life FSRP and 4.4 years for final FSRP measurement before death. Higher mid‐life vascular risk burden was associated with increased odds of all cerebrovascular pathology, even with adjustment for vascular risk burden before death. Late‐life vascular risk burden was associated with increased odds of cortical infarcts (OR [95% CI]: 1.04 [1.00, 1.08]) and arteriosclerosis stage (OR [95% CI]: 1.03 [1.00, 1.05]). Mid‐life vascular risk burden was not associated with Alzheimer’s disease pathology, though late‐life vascular risk burden was associated with increased odds of higher Braak stage (OR [95% CI]: 1.03 [1.01, 1.05]). Interpretation Mid‐life vascular risk burden was predictive of cerebrovascular but not Alzheimer’s disease neuropathology, even after adjustment for vascular risk factors before death.

Background Adipokines mediate cardiometabolic risk associated with obesity but their role in the pathogenesis of obesity‐associated heart failure remains uncertain. We investigated the associations between circulating adipokine concentrations and echocardiographic measures in a community‐based sample. Methods and Results We evaluated 3514 Framingham Heart Study participants (mean age 40 years, 53.8% women) who underwent routine echocardiography and had select circulating adipokines measured, ie, leptin, soluble leptin receptor, fatty acid–binding protein 4, retinol‐binding protein 4, fetuin‐A, and adiponectin. We used multivariable linear regression, adjusting for known correlates (including weight), to relate adipokine concentrations (independent variables) to the following echocardiographic measures (dependent variables): left ventricular mass index, left atrial diameter in end systole, fractional shortening, and E/e′. In multivariable‐adjusted analysis, left ventricular mass index was inversely related to circulating leptin and fatty acid–binding protein 4 concentrations but positively related to retinol‐binding protein 4 and leptin receptor levels (P≤0.002 for all). Left atrial end‐systolic dimension was inversely related to leptin but positively related to retinol‐binding protein 4 concentrations (P≤0.0001). E/e′ was inversely related to leptin receptor levels (P=0.0002). We observed effect modification by body weight for select associations (leptin receptor and fatty acid–binding protein 4 with left ventricular mass index, and leptin with left atrial diameter in end systole; P