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Background: American College of Cardiology/American Heart Association guidelines published in 2013 recommend high-intensity statins (atorvastatin 40 or 80 mg or rosuvastatin 20 or 40 mg) for most adults ≤75 years of age with atherosclerotic cardiovascular disease (ASCVD). For adults >75 years of age with ASCVD, the guidelines recommend continuation of tolerated statins or initiation of moderate intensity statins for most patients. Objective: To examine whether guideline concordant use of high-intensity statins following myocardial infarction (MI) among Medicare beneficiaries differed by hospital size, medical school affiliation, and region of the US in 2014 (after publication of the guidelines). Methods: We identified 28,086 Medicare beneficiaries with fee-for-service and pharmacy coverage who filled a statin within 30 days following hospital discharge for MI in 2014. The analyses were restricted to 731 hospitals with at least 20 beneficiaries discharged for MI in 2014. Hospital size and medical school affiliation were determined from the American Hospital Association survey. In subgroups ≤75 and >75 years of age, we calculated the proportion of beneficiaries whose first statin fill after MI was a high-intensity statin by hospital, hospital size, medical school affiliation, and region. Results: Among statin users ≤75 years of age, 10,696 (55%) beneficiaries filled a prescription for a high-intensity statin following MI. The percentage filling high-intensity statins range from 0-100% (25 th percentile 39%, 75 th percentile 69%) across hospitals. High-intensity statin use was more common following hospitalization at larger hospitals, hospitals with medical school affiliations, and those in New England ( Figure ). A lower percentage of Medicare beneficiaries >75 years of age filled high-intensity statins (n = 8,441, 44%), but patterns were similar across hospital characteristics and region. Conclusions: Similar patterns of high-intensity statin use were present among individuals ≤75 years of age, in whom high-intensity statin use is guideline concordant, and individuals >75 years of age, in whom high-intensity statin use is not necessarily guideline concordant, suggesting that variation in high-intensity statin prescriptions may not be directly related to close adherence to guidelines.

Background: High intensity statins have been shown to lower the risk of major cardiovascular events after an index myocardial infarction (MI). Studies have shown that women are less likely than men to receive cardiovascular risk reduction therapies but little is known about sex differences in high intensity statin use following hospital discharge for MI. Methods: We compared high intensity statin use following hospital discharge for MI in 2014 between men and women 19 to 64 years with commercial health insurance in the Marketscan database (n=7,089 men and 2,318 women) and Medicare beneficiaries ≥66 years (n=20,202 men and n=18,937 women). Patients were included if they filled a statin of any intensity within 30 days following hospital discharge. Statin fills were identified through pharmacy claims and high intensity statins included atorvastatin 40 or 80 mg and rosuvastatin 20 or 40 mg. Results: Among patients not taking statins prior to having an MI (n=6,303 in Marketscan and n=17,763 in Medicare), 69.4% of men and 62.4% of women (p-value <0.001) in the Marketscan database and 55.2% of men and 48.1% of women (p-value <0.001) with health insurance through Medicare initiated treatment with a high intensity statin. Among patients taking low or moderate intensity statins prior to having an MI (n=2,234 in Marketscan and n=16,818 in Medicare), 58.0% of men and 49.2% of women (p-value <0.001) in the Marketscan database and 38.2% of men and 31.7% of women (p-value <0.001) in Medicare titrated to a high intensity statin within 30 days of hospital discharge. After multivariable adjustment, women were less likely to initiate treatment with a high intensity statin (relative risk: 0.92; 95% CI 0.88-0.96 in Marketscan and 0.92; 95% CI 0.90-0.95 in Medicare) or titrate from low/moderate to high intensity statin (relative risk: 0.89 95% CI 0.81-0.95 in Marketscan and 0.89; 95% CI 0.86-0.93 in Medicare). Among those taking a high intensity statin prior to their MI (n=870 in Marketscan and n=4,558 in Medicare), 92.0% and 87.4% of men and women, respectively, in Marketscan (adjusted relative risk 0.95; 95% CI 0.90-1.01) and 91.5% and 88.1% of men and women, respectively, in Medicare (adjusted relative risk 0.97; 95% CI 0.95-0.99), remained on a high intensity statin following hospital discharge. Conclusions: Women are less likely than men to receive high intensity statins following hospital discharge for MI.

Background Having more vascular conditions, including coronary heart disease (CHD), cerebrovascular disease and lower extremity artery disease (LEAD), may increase the risk for atherosclerosis cardiovascular disease (ASCVD) events. Specific vascular conditions may increase the ASCVD event rate more than others. Purpose To compare the risk for future ASCVD events associated with the number and type of vascular conditions among adults with a history of CHD, cerebrovascular disease and/or LEAD. Methods We analyzed data from US adults ≥19 years of age with commercial or Medicare health insurance who had a history of CHD, cerebrovascular disease and/or LEAD as of December 31, 2014 (N=901,391). Individuals were followed through December 31, 2016 (median follow-up: 2 years) for ASCVD events, including myocardial infarction, coronary revascularization, stroke, carotid revascularization and lower extremity amputation or revascularization. Results Among individuals included in the current analysis (mean age 63 years, 45% female), 70%, 23% and 7% had 1, 2 and 3 vascular conditions, respectively. After adjustment for sociodemographic and cardiovascular risk factors, the hazard ratio for ASCVD among individuals with 2 and 3 versus 1 vascular conditions was 1.88 (1.85, 1.92) and 2.93 (2.86, 3.00), respectively. Among individuals with 1 vascular condition, the rate of ASCVD events per 1,000 person-years was 46.5 (95% CI 44.1, 49.0), 29.6 (95% CI 29.0, 30.1) and 19.9 (95% CI 19.2, 20.8) for those with LEAD, CHD and cerebrovascular disease, respectively. The multivariable-adjusted hazard ratio (95% CI) for ASCVD events comparing individuals with LEAD only and CHD only versus those with cerebrovascular disease only was 1.84 (1.77, 1.92) and 1.12 (1.08, 1.16), respectively. Among individuals with 2 vascular conditions, the ASCVD event rate per 1,000 person-years was higher in those with LEAD and CHD (122.0, 95% CI 112.5, 132.2) and with LEAD and cerebrovascular disease (92.4, 95% CI 79.9, 106.4), versus those with CHD and cerebrovascular disease (59.1, 95% CI 54.8, 63.6). The multivariable-adjusted hazard ratio (95% CI) comparing individuals with LEAD and CHD and those with LEAD and cerebrovascular disease versus those with CHD and cerebrovascular disease was 1.48 (1.44, 1.53) and 1.49 (1.41, 1.58), respectively. Conclusion Among adults with vascular disease, having LEAD confers a higher risk for future ASCVD events than CHD or cerebrovascular disease and this group may benefit from more intensive risk reduction treatment. Acknowledgement/Funding Amgen Inc.

Objective This study aimed to investigate a variety of machine learning (ML) methods to predict the association between cardiovascular risk factors and coronary artery disease-reporting and data system (CAD-RADS) scores. Methods This is a retrospective cohort study. Demographical, cardiovascular risk factors and coronary CT angiography (CCTA) characteristics of the patients were obtained. Coronary artery disease (CAD) was evaluated using CAD-RADS score. The stenosis severity component of the CAD-RADS was stratified into two groups: CAD-RADS score 0-2 group and CAD-RADS score 3–5 group. CAD-RADS scores were predicted with random forest (RF), k-nearest neighbors (KNN), support vector machines (SVM), neural network (NN), decision tree classification (DTC) and linear discriminant analysis (LDA). Prediction sensitivity, specificity, accuracy and area under the curve (AUC) were calculated. Feature importance analysis was utilized to find the most important predictors. Results A total of 442 CAD patients with CCTA examinations were included in this study. 234 (52.9%) subjects were CAD-RADS score 0–2 group and 208 (47.1%) were CAD-RADS score 3–5 group. CAD-RADS score 3-5 group had a high prevalence of hypertension (66.8%), hyperlipidemia (50%) and diabetes mellitus (DM) (35.1%). Age, systolic blood pressure (SBP), mean arterial pressure, pulse pressure, pulse pressure index, plasma fibrinogen, uric acid and blood urea nitrogen were significantly higher (p < 0.001), and high-density lipoprotein (HDL-C) lower (p < 0.001) in CAD-RADS score 3–5 group compared to the CAD-RADS score 0–2 group. Nineteen features were chosen to train the models. RF (AUC = 0.832) and LDA (AUC = 0.81) outperformed SVM (AUC = 0.772), NN (AUC = 0.773), DTC (AUC = 0.682), KNN (AUC = 0.707). Feature importance analysis indicated that plasma fibrinogen, age and DM contributed most to CAD-RADS scores. Conclusion ML algorithms are capable of predicting the correlation between cardiovascular risk factors and CAD-RADS scores with high accuracy.