Impact of Guideline-Directed Statin Intervention for Primary Prevention in Patients With Diabetes.

OBJECTIVE: We examined guideline-directed statin intensity (GDSI) use and atherosclerotic cardiovascular disease (ASCVD) outcomes in patients with diabetes across a contemporary health care system. RESEARCH DESIGN AND METHODS: Patients without preexisting ASCVD were categorized by diabetes status and 10-year ASCVD risk (borderline [5-7.4%], intermediate [7.5-19.9%], high [≥20%]). Mean ±SD time to start of or change to GDSI was calculated. Incident ASCVD and all-cause mortality association, stratified by ASCVD risk, was calculated using Cox regression. RESULTS: Among 282,298 patients, 28,807 (10.2%) had diabetes and 253,491 (89.8%) did not. Only two-thirds of intermediate- and high-risk patients with diabetes were receiving GDSI therapy at 5-year follow-up. In fully adjusted models, patients with diabetes not taking a statin (vs. GDSI) had a significantly higher risk of stroke and mortality in the intermediate- and high-risk groups (hazard ratio for mortality 1.81 [95% CI 1.58-2.07] vs. 1.41 [1.26-1.57]; P for interaction < 0.01). CONCLUSIONS: Significant gaps remain in GDSI use for high-risk patients with diabetes, conferring an increased risk of ASCVD outcomes and all-cause mortality.

Comparison of Atherosclerotic Cardiovascular Risk Factors and Cardiometabolic Profiles Between Current and Never Users of Marijuana.

BACKGROUND: The relationship between marijuana use and cardiovascular health remains uncertain, with several observational studies suggesting a potential association with increased adverse atherosclerotic cardiovascular disease (ASCVD) outcomes. This study examined the relationship between marijuana use, ASCVD risk factors, and cardiometabolic risk profiles. METHODS: US adults (18-59 years) without cardiovascular disease were identified from the National Health And Nutrition Examination Survey (2005-2018) based on self-reported marijuana use. Current users (used within the past month) and never users were compared with assess the burden and control of traditional ASCVD risk factors and biomarkers, using inverse probability of treatment weighting to adjust for sociodemographic and lifestyle factors, including tobacco use. RESULTS: Of the 13 965 participants identified (mean age, 37.5; 51.2% female; 13% non-Hispanic Black), 26.6% were current users. Current users were predominantly male, low-income, and more likely to be concurrent tobacco users. Inverse probability of treatment weighting analysis showed no significant differences in the burden and control of hypertension (19.3% versus 18.8%, P=0.76; 79.8% versus 77.8%, P=0.75), dyslipidemia (24.0% versus 19.9%, P=0.13; 82% versus 75%, P=0.95), diabetes (4.8% versus 6.4%, P=0.19; 52.9% versus 50.6%, P=0.84), obesity (35.8% versus 41.3%, P=0.13), and physical activity levels (71.9% versus 69.3%, P=0.37) between current and never users. Likewise, mean 10-year ASCVD risk scores (2.8% versus 3.0%, P=0.49), 30-year Framingham risk scores (22.7% versus 24.2%, P=0.25), and cardiometabolic profiles including high-sensitivity C-reactive protein (3.5 mg/L versus 3.7 mg/L, P=0.65), neutrophil-lymphocyte ratio (2.1 versus 2.1, P=0.89), low-density lipoprotein (114.3 mg/dL versus 112.2 mg/dL, P=0.53), total cholesterol (191.2 mg/dL versus 181.7 mg/dL, P=0.58), and hemoglobin A1C (5.4% versus 5.5%, P=0.25) were similar between current and never users. CONCLUSIONS: This cross-sectional study found no association between self-reported marijuana use and increased burden of traditional ASCVD risk factors, estimated long-term ASCVD risk, or cardiometabolic profiles. Further studies are needed to explore potential pathways between adverse cardiovascular disease outcomes and marijuana use.

Cardiovascular Disease Risk-Based Statin Utilization and Associated Outcomes in a Primary Prevention Cohort: Insights From a Large Health Care Network.

BACKGROUND: Current American College of Cardiology/American Heart Association guidelines recommend using the 10-year atherosclerotic cardiovascular disease (ASCVD) risk to guide statin therapy for primary prevention. Real-world data on adherence and consequences of nonadherence to the guidelines in primary are limited. We investigated the guideline-directed statin intensity (GDSI) and associated outcomes in a large health care system, stratified by ASCVD risk. METHODS: Statin prescription in patients without coronary artery disease, peripheral vascular disease, or ischemic stroke were evaluated within a large health care network (2013-2017) using electronic medical health records. Patient categories constructed by the 10-year ASCVD risk were borderline (5%-7.4%), intermediate (7.5%-19.9%), or high (≥20%). The GDSI (before time of first event) was defined as none or any intensity for borderline, and at least moderate for intermediate and high-risk groups. Mean (±SD) time to start/change to GDSI from first interaction in health care and incident rates (per 1000 person-years) for each outcome were calculated. Cox regression models were used to calculate hazard ratios for incident ASCVD and mortality across risk categories stratified by statin utilization. RESULTS: Among 282 298 patients (mean age ≈50 years), 29 134 (10.3%), 63 299 (22.4%), and 26 687 (9.5%) were categorized as borderline, intermediate, and high risk, respectively. Among intermediate and high-risk categories, 27 358 (43%) and 8300 (31%) patients did not receive any statin, respectively. Only 17 519 (65.6%) high-risk patients who were prescribed a statin received GDSI. The mean time to GDSI was ≈2 years among the intermediate and high-risk groups. At a median follow-up of 6 years, there was a graded increase in risk of ASCVD events in intermediate risk (hazard ratio=1.15 [1.07-1.24]) and high risk (hazard ratio=1.27 [1.17-1.37]) when comparing no statin use with GDSI therapy. Similarly, mortality risk among intermediate and high-risk groups was higher in no statin use versus GDSI. CONCLUSIONS: In a real-world primary prevention cohort, over one-third of statin-eligible patients were not prescribed statin therapy. Among those receiving a statin, mean time to GDSI was ≈2 years. The consequences of nonadherence to guidelines are illustrated by greater incident ASCVD and mortality events. Further research can develop and optimize health care system strategies for primary prevention.

Ideal Cardiovascular Health Metrics in Couples: A Community-Based Study.

BACKGROUND: Determination of the correlation of ideal cardiovascular health variables among spousal or cohabitating partners may guide the development of couple-based interventions to reduce cardiovascular disease risk. METHOD AND RESULTS: We used data from the HeartSCORE (Heart Strategies Concentrating on Risk Evaluation) study. Ideal cardiovascular health, defined by the American Heart Association, comprises nonsmoking, body mass index <25 kg/m2, physical activity at goal, diet consistent with guidelines, untreated total cholesterol <200 mg/dL, untreated blood pressure <120/80 mm Hg, and untreated fasting glucose <100 mg/dL. McNemar test and logistic regression were used to assess concordance patterns in these variables among partners (ie, concordance in achieving ideal factor status, concordance in not achieving ideal factor status, or discordance-only one partner achieving ideal factor status). Overall, there was a low prevalence of ideal cardiovascular health among the 231 couples studied (median age 61 years, 78% white). The highest concordances in achieving ideal factor status were for nonsmoking (26.1%), ideal fruit and vegetable consumption (23.9%), and ideal fasting blood glucose (35.6%). The strongest odds of intracouple concordance were for smoking (odds ratio, 3.6; 95% confidence interval, 1.9-6.5), fruit and vegetable consumption (odds ratio, 4.8; 95% confidence interval, 2.5-9.3) and blood pressure (odds ratio, 3.0; 95% confidence interval, 1.2-7.9). A participant had 3-fold higher odds of attaining ≥3 ideal cardiovascular health variables if he or she had a partner who attained ≥3 components (odds ratio 3.0; 95% confidence interval, 1.6-5.6). CONCLUSIONS: Intracouple concordance of ideal cardiovascular health variables supports the development and testing of couple-based interventions to promote cardiovascular health. Fruit and vegetable consumption and smoking may be particularly good intervention targets.

Traditional and nontraditional cardiovascular risk factors in comorbid insomnia and sleep apnea.

OBJECTIVES: Insomnia and sleep apnea frequently co-occur and are independently associated with an increased risk of cardiovascular disease, but little is known about cardiovascular disease risk among individuals with comorbid insomnia and sleep apnea. The current study examined traditional risk factors and a physiologic biomarker of cardiovascular risk in comorbid insomnia and sleep apnea. DESIGN: Community-based participatory research study. PARTICIPANTS: The sample comprised 795 participants without preexisting cardiovascular disease from the Heart Strategies Concentrating On Risk Evaluation (Heart SCORE) study. MEASUREMENTS AND RESULTS: Participants were assessed for symptoms of insomnia and sleep apnea risk, as well as for presence of obesity, smoking, a sedentary lifestyle, hypertension, dyslipidemia, and diabetes. Baseline resting brachial artery diameter was measured by B-mode ultrasonography. A total of 138 participants (17.4%) met criteria for insomnia syndrome alone, 179 (22.5%) were at high risk for sleep apnea alone, 95 (11.9%) reported both insomnia syndrome and high sleep apnea risk, and 383 (48.2%) reported having neither insomnia nor sleep apnea symptoms Both high sleep apnea risk alone and comorbid insomnia and high sleep apnea risk groups had greater frequencies of obesity, sedentary lifestyle, hypertension, and three or more traditional cardiovascular risk factors and significantly larger brachial artery diameters than the insomnia alone group and those without insomnia or sleep apnea symptoms. No differences in traditional cardiovascular risk factors or brachial artery diameter were found between the high sleep apnea risk and comorbid groups. CONCLUSIONS: These findings suggest that sleep apnea is a major contributor to cardiovascular risk and co-occurring insomnia does not appear to add to this risk.

Sociodemographic, clinical, and psychological factors associated with attrition in a prospective study of cardiovascular prevention: the Heart Strategies Concentrating on Risk Evaluation study.

PURPOSE: To identify factors associated with attrition in a longitudinal study of cardiovascular prevention. METHODS: Demographic, clinical, and psychosocial variables potentially associated with attrition were investigated in 1841 subjects enrolled in the southwestern Pennsylvania Heart Strategies Concentrating on Risk Evaluation study. Attrition was defined as study withdrawal, loss to follow-up, or missing 50% or more of study visits. RESULTS: Over 4 years of follow-up, 291 subjects (15.8%) met criteria for attrition. In multivariable regression models, factors that were independently associated with attrition were black race (odds ratio [OR], 2.21; 95% confidence interval [CI], 1.55-3.16; P < .001), younger age (OR per 5-year increment, 0.88; 95% CI, 0.79-0.99; P < .05), male gender (OR, 1.79; 95% CI, 1.27-2.54; P < .05), no health insurance (OR, 2.04; 95% CI, 1.20-3.47; P < .05), obesity (OR, 1.80; 95% CI, 1.07-3.02; P < .05), CES-D depression score 16 or higher (OR, 2.02; 95% CI, 1.29-3.19; P < .05), and higher ongoing life events questionnaire score (OR, 1.09; 95% CI, 1.04-1.13; P < .001). Having a spouse/partner participating in the study was associated with lower odds of attrition (OR, 0.60; 95% CI, 0.37-0.97; P < .05). A synergistic interaction was identified between black race and depression. CONCLUSIONS: Attrition over 4 years was influenced by sociodemographic, clinical, and psychological factors that can be readily identified at study entry. Recruitment and retention strategies targeting these factors may improve participant follow-up in longitudinal cardiovascular prevention studies.