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Background We examined the interplay of apolipoprotein B (apoB) and LDL particle size, approximated by the LDL-cholesterol (LDL-C)/apoB ratio, on the risk of new-onset coronary heart disease (CHD). Methods Participants without cardiovascular disease from the UK Biobank (UKB; n = 308 182), the Women’s Health Study (WHS; n = 26 204), and the Framingham Heart Study (FHS; n = 2839) were included. Multivariable Cox models were used to assess the relationship between apoB and LDL-C/apoB ratio and incidence of CHD (14 994 events). Our analyses were adjusted for age, sex (except WHS), HDL-cholesterol (HDL-C), systolic blood pressure, antihypertensive treatment, diabetes, and smoking. Results In all 3 studies, there was a strong positive correlation between apoB and LDL-C (correlation coefficients r = 0.80 or higher) and a weak inverse correlation of apoB with LDL-C/apoB ratio (−0.28 ≤ r ≤ −0.14). For all 3 cohorts, CHD risk was higher for higher levels of apoB. Upon multivariable adjustment, the association between apoB and new-onset CHD remained robust and statistically significant in all 3 cohorts with hazard ratios per 1 SD (95% CI): 1.24 (1.22–1.27), 1.33 (1.20–1.47), and 1.24 (1.09–1.42) for UKB, WHS, and FHS, respectively. However, the association between LDL-C/apoB and CHD was statistically significant only in the FHS cohort: 0.78 (0.64–0.94). Conclusions Our analysis confirms that apoB is a strong risk factor for CHD. However, given the null association in 2 of the 3 studies, we cannot confirm that cholesterol-depleted LDL particles are substantially more atherogenic than cholesterol-replete particles. These results lend further support to routine measurement of apoB in clinical care.

Background: Understanding the predictive utility of previously derived polygenic risk scores (PRSs) for long-term risk of coronary heart disease (CHD) and its additive value beyond traditional risk factors can inform prevention strategies. Methods: Data from adults 20 to 59 years of age who were free of CHD from the FOS (Framingham Offspring Study) and the ARIC (Atherosclerosis Risk in Communities) study were analyzed. Because the PRS was derived from samples of predominantly European ancestry, individuals who self-reported White race were included. The sample was stratified by age and cohort: young (FOS, 20–39 years [median, 30 years] of age), early midlife (FOS, 40–59 years [median, 43] years of age), and late midlife (ARIC, 45–59 years [median, 52 years] of age). Two previously derived and validated prediction tools were applied: (1) a 30-year traditional risk factor score and (2) a genome-wide PRS comprising >6 million genetic variants. Hazard ratios for the association between each risk estimate and incident CHD were calculated. Predicted and observed rates of CHD were compared to assess discrimination for each model individually and together with the optimism-corrected C index (95% CI). Results: Among 9757 participants, both the traditional risk factor score (hazard ratio per 1 SD, 2.60 [95% CI, 2.08–3.27], 2.09 [95% CI, 1.83–2.40], and 2.11 [95% CI, 1.96–2.28]) and the PRS (hazard ratio, 1.98 [95% CI, 1.70–2.30], 1.64 [95% CI, 1.47–1.84], and 1.22 [95% CI, 1.15–1.30]) were significantly associated with incident CHD in young, early midlife, and late midlife, respectively. Discrimination was similar or better for the traditional risk factor score (C index, 0.74 [95% CI, 0.70–0.78], 0.70 [95% CI, 0.67–0.72], and 0.72 [95% CI, 0.70–0.73]) compared with an age- and sex-adjusted PRS (0.73 [95% CI, 0.69–0.78], 0.66 [95% CI, 0.62–0.69], and 0.66 [95% CI, 0.64–0.67]) in young, early-midlife, and late-midlife participants, respectively. The ΔC index when PRS was added to the traditional risk factor score was 0.03 (95% CI, 0.001–0.05), 0.02 (95% CI, −0.002 to 0.037), and 0.002 (95% CI, −0.002 to 0.006) in young, early-midlife, and late-midlife participants, respectively. Conclusions: Despite a statistically significant association between PRS and 30-year risk of CHD, the C statistic improved only marginally with the addition of PRS to the traditional risk factor model among young adults and did not improve among midlife adults. PRS, an immutable factor that cannot be directly intervened on, has minimal clinical utility for long-term CHD prediction when added to a traditional risk factor model.

ImportancePrimary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation.ObjectiveTo determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population.Design, Setting, and ParticipantsThis was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023.ExposuresPRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status.Main Outcomes and MeasuresIncident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events.ResultsA total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, −0.07% to 3.30%).Conclusions and RelevanceStudy results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.

This study examines the risk of new-onset diabetes in patients with hypertriglyceridaemic hyperapolipoprotein B (high triglycerides, high apolipoprotein B [apoB], low LDL cholesterol to apoB ratio, and low HDL cholesterol). The aim was to establish whether this lipoprotein phenotype identified a substantial group at high risk of developing diabetes over the next 20 years.In this prospective, longitudinal, observational cohort study, we used data from the Framingham Offspring cohort (recruited in Framingham, MA, USA). Participants were aged 40-69 years and free of diabetes and cardiovascular disease at a baseline examination done between April, 1987, and November, 1991, and were followed up until March, 2014. Cox proportional hazards regression with hierarchical adjustment for age and sex, waist circumference, and fasting blood glucose were used to model the relationship between each lipid marker and incident diabetes, as well as the relationship between hypertriglyceridaemic hyperapoB (defined as values greater than sample medians of triglycerides and apoB, and less than medians of HDL cholesterol and LDL cholesterol to apoB ratio) and incident diabetes.Of 3446 individuals aged 40-69 years who completed baseline examination, 2515 participants were eligible and included in all analyses. During median 21·1 years (IQR 11·1-23·1) of follow-up, 402 (16·0%) individuals developed diabetes. Age (p=0·032), waist circumference (p0·0001), fasting blood glucose (p0·0001), and natural logarithm-transformed triglycerides (p0·0001) were associated with new-onset diabetes, as were apoB (p=0·0016), LDL cholesterol to apoB ratio (p=0·0018), and HDL cholesterol (p=0·0016) when added to this model. The age and sex-adjusted incidence of diabetes in the hypertriglyceridaemic hyperapoB group was 32·4% (95% CI 27·8-37·7) versus 5·5% (3·5-8·6) in the optimal lipid phenotype group and 15·5% (13·5-17·7) in the mixed lipid phenotype group. The fully adjusted hazard ratio, including glucose and waist circumference, for individuals with hypertriglyceridaemic hyperapoB was 3·30 (95% CI 2·06-5·30; p=0·0008) and for mixed lipid phenotype was 2·17 (1·38-3·40; p0·0001) compared with those with the optimal lipid phenotype.Our findings suggest that individuals with hypertriglyceridaemic hyperapoB are at high risk of new-onset diabetes and might benefit from intensive measures to prevent diabetes. The association between this phenotype and incident diabetes is consistent with a pro-diabetic effect due to increased clearance of apoB particles from plasma, which could injure pancreatic islet cells. This mechanism might explain the increased risk of diabetes with statin therapy.Doggone Foundation.

All the major lipid prevention guidelines agree that the 10-year risk of a cardiovascular event should be the primary method to select individuals for statin prevention of a cardiovascular event. They also all rely on LDL cholesterol (LDL-C) as the primary metric to monitor lipid lowering therapy. These two principles form the major instruments on which primary prevention of cardiovascular disease is based worldwide. Their application is based on decades of prospective observational studies and large numbers of randomized clinical trials. Their development and application are milestones in medical progress. But are there limits, which were unseen and unintended, that need to be identified and overcome so that cardiovascular prevention can improve? Based on new insights and old knowledge, this Viewpoint will apply Clinical Reasoning, the process by which we integrate all the relevant knowledge, including the knowledge we have gained from physiology, pathology, epidemiology, metabolism, experimental models of disease, and our clinical experience as well as the results of randomized clinical trials to the analysis of a single case to answer these questions. Moreover, this Viewpoint will challenge the universal practice of relating the clinical outcomes of the major successful lipid lowering trials to the decrease in LDL-C and argue that cardiovascular prevention should move from the Risk model to the Causal Benefit model. This Viewpoint will be framed around a single case because, as caregivers, we make decisions case by case and because, as caregivers, the individual is the true object of our concern.

Aims The aim of our study was to analyse the benefits of a 9 week hybrid comprehensive telerehabilitation (HCTR) programme in heart failure (HF) patients according to aetiology, as a subanalysis of the Telerehabilitation in Heart Failure Patients (TELEREH‐HF) trial. Methods and results Overall, 555 (65.3%) patients with ischaemic (IS) and 295 (34.7%) patients with non‐ischaemic (NIS) HF aetiology were randomized. There were no differences between the effect of HCTR and usual care (UC) on the primary outcome of number of days alive and out of the hospital in 26 months from the time of randomization in either aetiology (Wilcoxon–Mann–Whitney test), and no heterogeneity of effect between the aetiologies was noted (van Elteren test, P = 0.746). In Cox proportional hazards regression analysis, treatment was not independently associated with the secondary outcomes. For all‐cause mortality, the adjusted hazard ratio for HCTR vs. UC was 0.90 (95% confidence interval, 0.54–1.51) in IS and 1.42 (95% confidence interval, 0.69–2.94) in NIS (P interaction = 0.316). Differences between HCTR and UC in terms of change in the 6 min walk test distance and cardiopulmonary exercise test time after 9 weeks reached statistical significance in the IS arm (P = 0.015 and P

Introduction This study examines the dose–response relationship between moderate-to-vigorous physical activity and cardiometabolic measures in adolescents. Methods Cross-sectional spline analyses were performed using 2003–2016 National Health and Nutrition Examination Survey data among adolescents (aged 12–19 years, N=9,195) on objectively measured (2003–2006) and self-reported (2007–2016) weekly mean minutes of moderate-to-vigorous physical activity and cardiometabolic measures (systolic and diastolic blood pressure, total cholesterol, high-density lipoprotein, BMI, and cardiorespiratory fitness). Inflection points were determined for nonlinear relationships. Results For objective moderate-to-vigorous physical activity, female adolescents had significant nonlinear associations with inflection points at 90 minutes/week for BMI percentile and systolic blood pressure. Male adolescents had inflection points at 150 weekly minutes of objective activity for BMI percentile and cardiorespiratory fitness. BMI percentile was about 7% lower for female and male adolescents at 150 weekly minutes of objectively measured moderate-to-vigorous physical activity than at 0 minutes. For self-reported moderate-to-vigorous physical activity, inflection points were at 375 minutes/week (diastolic blood pressure for female adolescents) and 500 minutes/week (systolic blood pressure for male adolescents). Conclusions Among several significant dose–response relationships between physical activity and cardiometabolic health in adolescents, consistent and often nonlinear relationships were identified for BMI, with inflection points at 90–150 minutes of objective moderate-to-vigorous physical activity. Notable differences in associations and linearity were identified by sex and physical activity measure (objective or self-reported). These results support calls for any increase in physical activity among adolescents and suggest that recommendations closer to the adult guidelines of 150 weekly minutes of physical activity may be health promoting and more attainable for youth than the current recommendation of 420 weekly minutes.

Aims: The objective of the study was to evaluate the effects of individually prescribed hybrid comprehensive telerehabilitation (HCTR) implemented at patients’ homes on left ventricular (LV) diastolic function in heart failure (HF) patients. Methods and results: The Telerehabilitation in Heart Failure Patients trial (TELEREH-HF) is a multicenter, prospective, randomized (1:1), open-label, parallel-group, controlled trial involving HF patients assigned either to HCTR involving a remotely monitored home training program in conjunction with usual care (HCTR group) or usual care only (UC group). The patient in the HCTR group underwent a 9-week HCTR program consisting of two stages: an initial stage (1 week) conducted in hospital and the subsequent stage (eight weeks) of home-based HCTR five times weekly. Due to difficulties of proper assessment and differences in the evaluation of diastolic function in patients with atrial fibrillation, we included in our subanalysis only patients with sinus rhythm. Depending on the grade of diastolic dysfunction, patients were assigned to subgroups with mild diastolic (MDD) or severe diastolic dysfunction (SDD), both in HCTR (HCTR-MDD and HCTR-SDD) and UC groups (UC-MDD and UC-SDD). Changes from baseline to 9 weeks in echocardiographic parameters were seen only in A velocities in HCTR-MDD vs. UC-MDD; no significant shifts between groups of different diastolic dysfunction grades were observed after HCTR. All-cause mortality was higher in UC-SDD vs. UC-MDD with no difference between HCTR-SDD and HCTR-MDD. Higher probability of HF hospitalization was observed in HCTR-SDD than HCTR-MDD and in UC-SDD than UC-MDD. No differences in the probability of cardiovascular mortality and hospitalization were found. Conclusions: HCTR did not influence diastolic function in HF patients in a significant manner. The grade of diastolic dysfunction had an impact on mortality only in the UC group and HF hospitalization over a 12–24-month follow-up in HCTR and UC groups.

Artificial intelligence/machine learning models are being rapidly developed and used in clinical practice. However, many models are deployed without a clear understanding of clinical or operational impact and frequently lack monitoring plans that can detect potential safety signals. There is a lack of consensus in establishing governance to deploy, pilot, and monitor algorithms within operational healthcare delivery workflows. Here, we describe a governance framework that combines current regulatory best practices and lifecycle management of predictive models being used for clinical care. Since January 2021, we have successfully added models to our governance portfolio and are currently managing 52 models.

Background: Lipid-lowering recommendations for prevention of atherosclerotic cardiovascular disease rely principally on estimated 10-year risk. We sought to determine the optimal time for initiation of lipid lowering in younger adults as a function of expected 30-year benefit. Methods: Data from 3148 National Health and Nutrition Examination Survey (2009–2016) participants, age 30 to 59 years, not eligible for lipid-lowering treatment recommendation under the most recent US guidelines, were analyzed. We estimated the absolute and relative impact of lipid lowering as a function of age, age at initiation, and non–high-density lipoprotein cholesterol (HDL-C) level on the expected rates of atherosclerotic cardiovascular disease over the succeeding 30 years. We modeled expected risk reductions based on shorter-term effects observed in statin trials (model A) and longer-term benefits based on Mendelian randomization studies (model B). Results: In both models, potential reductions in predicted 30-year atherosclerotic cardiovascular disease risk were greater with older age and higher non–HDL-C level. Immediate initiation of lipid lowering (ie, treatment for 30 years) in 40- to 49-year-old patients with non–HDL-C ≥160 mg/dL would be expected to reduce their average predicted 30-year risk of 17.1% to 11.6% (model A; absolute risk reduction [ARR], 5.5%) or 6.5% (model B; ARR 10.6%). Delaying lipid lowering by 10 years (treatment for 20 years) would result in residual 30-year risk of 12.7% (A; ARR 4.4) or 9.9% (B; ARR 7.2%) and delaying by 20 years (treatment for 10 years) would lead to expected mean residual risk of 14.6% (A; ARR 2.6%) or 13.9% (B; ARR 3.2%). The slope of the achieved ARR as a function of delay in treatment was also higher with older age and higher non–HDL-C level. Conclusions: Substantial reduction in expected atherosclerotic cardiovascular disease risk in the next 30 years is achievable by intensive lipid lowering in individuals in their 40s and 50s with non–HDL-C ≥160 mg/dL. For many, the question of when to start lipid lowering might be more relevant than whether to start lipid lowering.

Purpose Guidelines recommend 150 minutes of weekly moderate-to-vigorous physical activity (MVPA) for all adults, although physical activity level correlation with cardiometabolic health is not well characterized for young adults. We determined the dose–response relationship of MVPA on measures of cardiometabolic health in young adults. Methods We examined young adults (aged 20–29 years; N = 5,395, 47.9% female) in the 2003–2016 National Health and Nutrition Examination Survey. Exposures were objective (accelerometer based) and self-reported weekly mean minutes of MVPA. Cardiometabolic outcome measures were body mass index (BMI), high-density lipoprotein (HDL), total cholesterol, systolic blood pressure, and diastolic blood pressure. The dose–response relationships were assessed with unadjusted spline analyses. Sex-stratified outcomes were modeled using multivariable linear regression with mean estimated change presented for 150-minute dose increases of MVPA. Results Among females, associations between objective activity and cardiometabolic measures were all linear. Compared with no activity, 150 minutes of objective activity was associated with a lower BMI (−1.37 kg/m2) and total cholesterol (−4.89 mg/dL), whereas 150 minutes of self-reported activity was associated with a higher HDL (1 mg/dL) and lower diastolic blood pressure (−.42 mm Hg). Among males, an inflection point was identified in the dose–response curves for objective activity with BMI around 100 minutes. Compared with no activity, 150 self-reported minutes was associated with lower BMI (−.26 kg/m2), higher HDL (.52 mg/dL), and lower total cholesterol (−1.35 mg/dL). Conclusions The dose–response relationships between physical activity and cardiometabolic markers in young adults were predominantly linear, supporting public health calls for any increase in physical activity in this population.

The Project Baseline Health Study (PBHS) was launched to map human health through a comprehensive understanding of both the health of an individual and how it relates to the broader population. The study will contribute to the creation of a biomedical information system that accounts for the highly complex interplay of biological, behavioral, environmental, and social systems. The PBHS is a prospective, multicenter, longitudinal cohort study that aims to enroll thousands of participants with diverse backgrounds who are representative of the entire health spectrum. Enrolled participants will be evaluated serially using clinical, molecular, imaging, sensor, self-reported, behavioral, psychological, environmental, and other health-related measurements. An initial deeply phenotyped cohort will inform the development of a large, expanded virtual cohort. The PBHS will contribute to precision health and medicine by integrating state of the art testing, longitudinal monitoring and participant engagement, and by contributing to the development of an improved platform for data sharing and analysis.

Prediction Models Prediction models’ newfound importance and the emergence of model development based on machine learning raise questions about how to ensure their safety and efficacy, given their ...

ImportanceStroke is the fifth-highest cause of death in the US and a leading cause of serious long-term disability with particularly high risk in Black individuals. Quality risk prediction algorithms, free of bias, are key for comprehensive prevention strategies.ObjectiveTo compare the performance of stroke-specific algorithms with pooled cohort equations developed for atherosclerotic cardiovascular disease for the prediction of new-onset stroke across different subgroups (race, sex, and age) and to determine the added value of novel machine learning techniques.Design, Setting, and ParticipantsRetrospective cohort study on combined and harmonized data from Black and White participants of the Framingham Offspring, Atherosclerosis Risk in Communities (ARIC), Multi-Ethnic Study for Atherosclerosis (MESA), and Reasons for Geographical and Racial Differences in Stroke (REGARDS) studies (1983-2019) conducted in the US. The 62 482 participants included at baseline were at least 45 years of age and free of stroke or transient ischemic attack.ExposuresPublished stroke-specific algorithms from Framingham and REGARDS (based on self-reported risk factors) as well as pooled cohort equations for atherosclerotic cardiovascular disease plus 2 newly developed machine learning algorithms.Main Outcomes and MeasuresModels were designed to estimate the 10-year risk of new-onset stroke (ischemic or hemorrhagic). Discrimination concordance index (C index) and calibration ratios of expected vs observed event rates were assessed at 10 years. Analyses were conducted by race, sex, and age groups.ResultsThe combined study sample included 62 482 participants (median age, 61 years, 54% women, and 29% Black individuals). Discrimination C indexes were not significantly different for the 2 stroke-specific models (Framingham stroke, 0.72; 95% CI, 0.72-073; REGARDS self-report, 0.73; 95% CI, 0.72-0.74) vs the pooled cohort equations (0.72; 95% CI, 0.71-0.73): differences 0.01 or less (P values >.05) in the combined sample. Significant differences in discrimination were observed by race: the C indexes were 0.76 for all 3 models in White vs 0.69 in Black women (all P values P values ≤.001). When stratified by age, model discrimination was better for younger (Conclusions and RelevanceIn this analysis of Black and White individuals without stroke or transient ischemic attack among 4 US cohorts, existing stroke–specific risk prediction models and novel machine learning techniques did not significantly improve discriminative accuracy for new-onset stroke compared with the pooled cohort equations, and the REGARDS self-report model had the best calibration. All algorithms exhibited worse discrimination in Black individuals than in White individuals, indicating the need to expand the pool of risk factors and improve modeling techniques to address observed racial disparities and improve model performance.

Background Medicare insurance claims may provide an efficient means to ascertain follow-up of older participants in clinical research. We sought to determine the accuracy and completeness of claims- versus site-based follow-up with clinical event committee (+CEC) adjudication of cardiovascular outcomes. Methods We performed a retrospective study using linked Medicare and Duke Database of Clinical Trials data. Medicare claims were linked to clinical data from 7 randomized cardiovascular clinical trials. Of 52,476 trial participants, linking resulted in 5,839 (of 10,497 linkage-eligible) Medicare-linked trial participants with fee-for-service A and B coverage. Death, myocardial infarction (MI), stroke, and revascularization incidences were compared using Medicare inpatient claims only, site-reported events (+CEC) only, or a combination of the 2. Randomized treatment effects were compared as a function of whether claims-based, site-based (+CEC), or a combined system was used for event detection. Results Among the 5,839 study participants, the annual event rates were similar between claims- and site-based (+CEC) follow-up: death (overall rate 5.2% vs 5.2%; adjusted κ 0.99), MI (2.2% vs 2.3%; adjusted κ 0.96), stroke (0.7% vs 0.7%; adjusted κ 0.99), and any revascularization (7.4% vs 7.9%; adjusted κ 0.95). Of events detected by claims yet not reported by CEC, a minority were reported by sites but negatively adjudicated by CEC (39% of MIs and 18% of strokes). Differences in individual case concordance led to higher event rates when claims- and site-based (+CEC) systems were combined. Randomized treatment effects were similar among the 3 approaches for each outcome of interest. Conclusions Claims- versus site-based (+CEC) follow-up identified similar overall cardiovascular event rates despite meaningful differences in the events detected. Randomized treatment effects were similar using the 2 methods, suggesting claims data could be used to support clinical research leveraging routinely collected data. This approach may lead to more effective evidence generation, synthesis, and appraisal of medical products and inform the strategic approaches toward the National Evaluation System for Health Technology.

Background There is a paucity of data on the distribution of cardiovascular risk factors in patients with familial hypercholesterolemia (FH) as compared to the general population. The aim of the study was to compare cardiovascular risk factors in a cohort of FH patients to the representative sample of adults in Poland who represent a high–cardiovascular risk European region. Methods We compared the distribution of risk factors in 1,382 individuals with FH phenotype referred for genetic testing between 2006 and 2014 to the National Centre of Familial Hypercholesterolemia in Gdansk, Poland. The cohort was comprised of 637 positive FH(+) and 745 negative FH(−) patients who were compared to a nationally representative sample of 2,413 adults age 18-79, standardized by age and sex, from the NATPOL 2011 study (NATPOL). We analyzed patients' distribution of history of atherosclerotic cardiovascular disease (ASCVD) and standard risk factors including total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, triglycerides, systolic and diastolic blood pressure (SBP, DBP), body mass index, smoking, and diabetes. Results FH(+) patients (mean age 45.6 years) had the highest LDL-C of 241.7 mg/dL (95% CI 234.8-248.5) compared to 206.1 mg/dL (200.5-211.7) in FH(−) patients (mean age 48.2) and 126.2 mg/dL (124.8-127.6) in NATPOL. Mean SBP was the lowest in FH(+) patients at 128.7 mm Hg (126.7-130.7) compared to 133.4 mm Hg (132.6-134.3) in NATPOL and 134.4 mm Hg (132.3-136.5) in FH(−). No differences were found in the prevalence of diabetes and body mass index. Smoking was less common in FH(+) at 12.4% (9.4-15.4) compared to both FH(−) and NATPOL: 20.4% (16.6-24.1) and 28.4% (26.6-30.2), respectively. The prevalence of individuals with a history of ASCVD in both FH(+) and FH(−) was nearly 3-fold higher compared to NATPOL: 26% (21.8-30.1) and 26.6% (22.2-30.9) versus 9.5% (8.3-10.7), respectively. Conclusions The FH(+) patients had significantly higher mean LDL-C, but the levels of nonlipid factors were lower or similar compared to the other groups. Both FH(+) and FH(−) were characterized by a heavy burden of ASCVD. This suggests that cholesterol, and no other risk factors, is a key contributor to cardiovascular risk in patients with FH, especially those with genetic mutation.

Background Guidelines recommend exercise training as a component of heart failure (HF) management. There are large disparities in access to rehabilitation and introducing hybrid comprehensive telerehabilitation (TR) consisting of remote monitoring of training in patients' homes might be an optimal solution in Poland. Purpose The primary objective of the TELEREH-HF trial is to determine whether introducing TR will significantly increase days alive and out of hospital compared with usual care. The secondary objectives including assessment the effects of TR compared to usual care on all-cause and cardiovascular mortality and all-cause, cardiovascular and HF hospitalization. The tertiary analyses include: evaluation of the safety, effectiveness, quality of life, depression, anxiety, patients' acceptance of and adherence to TR. Methods The TELEREH-HF study is a randomized, multi-center, prospective, open-label, parallel group controlled trial in 850 HF patients after a hospitalization incident in NYHA I-III and LVEF≤40%. Patients were randomized to TR + usual care (TR group) or to usual care only (control group) and are followed for a maximum of 24 months. The TR group patients underwent a 9-week TR program consisting of an initial stage (1 week) conducted at hospital and a basic stage (8-week) home-based TR five times weekly. Results All patients were randomized and completed initial intervention in the TR group. The follow up of both groups is in progress. Conclusion The TELEREH-HF trial will provide novel data on the effects of telerhabilitation on hospitalization and mortality in HF patients, and on safety, qaulity of life, depression, anxiety and acceptance of and adherence to this intervention.

The prediction of myocardial infarction (MI), acute ischemic stroke (AIS), cardiovascular (CVD) death, and 3-point MACE (MI, AIS, or CVD death) in Million Veteran Program (MVP) participants over 8 years of follow up was evaluated using environmental/traditional risk factors (“E”), polygenic risk scores (“G”), and a combination of both approaches (“GxE”). Individuals free of atherosclerotic cardiovascular disease (ASCVD) at baseline were included. Risk factor levels for the participants close to the time of MVP enrollment for age, sex, systolic blood pressure, cholesterol, HDL cholesterol, smoking status, and diabetes status were analyzed. Outcomes were determined from VA electronic record data, Medicare/Medicaid data, and the National Death Index. Analyses were undertaken separately for non-Hispanic European (EUR), African American (AFR), and Hispanic (HIS) participants. There were 157,941 veterans at risk with 8,157 MI events, 2,024 AIS events, 1,778 CVD deaths, and 9,350 3-pt MACE events over 8 years of follow-up. The overall results showed good performance with the environmental model for all three racial-ethnic groups, with C-statistics ranging from 0.69 to 0.77. The G models showed very modest prediction capabilities and similarly modest improvement in the combined GxE models. In conclusion, traditional risk factor modeling has been shown to be highly effective and, in the MVP experience, the additional impact of genetic or genetic interaction information was small.

There is a need to identify high-risk features that predict early-onset atherosclerotic cardiovascular disease (ASCVD). The authors provide insights to help clinicians identify and address high-risk conditions in the 20- to 39-year age range (young adults). These include tobacco use, elevated blood pressure/hypertension, family history of premature ASCVD, primary severe hypercholesterolemia such as familial hypercholesterolemia, diabetes with diabetes-specific risk-enhancing factors, or the presence of multiple other risk-enhancing factors, including in females, a history of pre-eclampsia or menopause under age 40. The authors update current thinking on lipid risk factors such as triglycerides, non-high-density lipoprotein cholesterol, apolipoprotein B, or lipoprotein (a) that are useful in understanding an individual's long-term ASCVD risk. The authors review emerging strategies, such as coronary artery calcium and polygenic risk scores in this age group, that have potential clinical utility, but whose best use remains uncertain. Finally, the authors discuss both the obstacles and opportunities for addressing prevention in early adulthood.

Background Exercise training in heart failure (HF) patients should be monitored to ensure patients’ safety. Electrocardiographic (ECG) telemonitoring was used to assess the safety of hybrid comprehensive telerehabilitation (HCTR). Objective Analysis of ECG recorded during HCTR in HF patients. Methods The TELEREH‐HF multicenter, randomized, controlled trial enrolled 850 HF patients with New York Heart Association class I‐III and left ventricular ejection fraction of ≤40%. This subanalysis focuses on 386 patients (aged 62 ± 11 years, LVEF 31 ± 7%) randomized to HCTR. HCTR was telemonitored with a device allowing to record 16‐s fragments of ECG and to transmit the data via mobile phone network to the monitoring center. ResultsIn 386 patients, 16,622 HCTR sessions were recorded and 66,488 ECGs fragments were evaluated. Sinus rhythm was present in 320 (83%) and permanent atrial fibrillation (AF) in 66 (17%) patients, respectively. The most common arrhythmias were ventricular and atrial premature beats, recorded in 76.4% and 27.7% of the patients, respectively. Non‐sustained ventricular tachycardia (21 episodes in 8 patients) and paroxysmal AF episodes (6 in 4 patients) were rare. None of the analyzed demographic and clinical characteristics was predictive for onset of the new arrhythmias on exercise. Conclusion Telerehabilitation in HF patients was safe without the evidence for symptomatic arrhythmias requiring discontinuation of telerehabilitation. Only one mildly symptomatic paroxysmal AF episode led to the short‐term suspension of the training program. The most common arrhythmias were atrial and ventricular premature beats. These arrhythmias did not result in any changes in rehabilitation and therapy regimens.

Introduction The novel hybrid comprehensive telerehabilitation (HCTR) consisting of telecare (with psychological telesupport), telerehabilitation and remote monitoring of cardiovascular implantable electronic devices might be an option to improve both physical capacity and depressive symptoms. Purpose The aim of the study was to investigate the influence of HCTR on depressive symptoms and physical capacity in heart failure (HF) patients in comparison with usual care (UC) alone. Methods The present analysis formed part of a multicenter, randomized trial that enrolled 850 HF patients (New York Heart Association class I–III, left ventricular ejection fraction ≤40%). Patients were randomized 1:1 to HCTR plus UC or UC only. Patients underwent either an HCTR program (1 week in hospital and 8 weeks at home; exercise training 5 times weekly) or UC with observation. The psychological intervention in the HCTR group included supportive psychological counseling via mobile phone. The Beck Depression Inventory II (BDI II) score (cut point for depression ≥14) was used to assess depression and the physical capacity was measured by peak oxygen consumption (peak VO2). Measurements were made before and after a 9-week intervention (HCTR group)/ observation (UC group). Results Both groups were comparable in terms of demographic, clinical characteristics and medical therapy. In HCTR group at entry 23% of the sample (n=88/382) obtaining BDI-II scores ≥14 vs 27.5% (n=107/389) in UC group. The BDI II score at study entry was 9.8±6.6 and after intervention was 9.2±6.6, p=0.016 (HCTR group) vs at entry 10.6±8.2 and after observation 10.0±8.3, p=0.022 (UC group). There were no significant differences between groups regarding ΔBDI II score p=0.992. There was a significant improvement in physical capacity assessed by peak VO2 only in the HCTR group, both in patients with (p=0.033) and without (p Conclusions In heart failure patients, HCTR provided similar reduction of depressive symptoms as UC. Hybrid comprehensive telerehabilitation resulted in a significant improvement in physical capacity both in patients with and without depression. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): The National Centre for Research and Development, Warsaw, Poland.

IntroductionCardiac rehabilitation is a component of heart failure (HF) management, but its effect on ventricular arrhythmias is not well understood. We analyzed the antiarrhythmic effect of a 9-week hybrid comprehensive telerehabilitation (HCTR) program and its influence on long-term cardiovascular mortality in HF patients taken from the TELEREHabilitation in Heart Failure Patients (TELEREH-HF) trial.Material and methodsWe evaluated the presence of non-sustained ventricular tachycardia (nsVT) and frequent premature ventricular complexes ≥ 10 beats/hour (PVCs ≥ 10) in 24-hour ECG monitoring at baseline and after 9-week HCTR or usual care (UC) of 773 HF patients (NYHA I-III, LVEF ≤ 40%). Functional response for HCTR was assessed by changes – delta () – in peak oxygen consumption (pVO2) as a result of comparing pVO2 from the beginning and the end of the program.ResultsAmong 143 patients with nsVT, arrhythmia subsided in 30.8% after HCTR. Similarly, among 165 patients randomized to UC who had nsVT 34.5% did not show it after 9 weeks (p = 0.481). There was no significant difference in the decrease in PVC ≥ 10 over 9 weeks between randomization arms (14.9% vs. 17.8%, respectively p = 0.410). Functional response for HCTR in ΔpVO2 > 2.0 ml/kg/min did not affect occurrence of arrhythmias. Multivariable analysis did not identify HCTR as an independent factor determining improvement of nsVT or PVCs ≥ 10. However, only in the HCTR group, the achievement of the antiarrhythmic effect significantly reduced the cardiovascular mortality in 2-year follow-up (p < 0.001).ConclusionsSignificant improvement in physical capacity after 9 weeks of HCTR did not correlate with the antiarrhythmic effect in terms of incidence of nsVT or PVCs ≥ 10. An antiarrhythmic effect after the 9-week HCTR affected long-term cardiovascular mortality in HF patients.

BACKGROUND: The appropriate dose of aspirin to lower the risk of death, myocardial infarction, and stroke and to minimize major bleeding in patients with established atherosclerotic cardiovascular disease is a subject of controversy. METHODS: Using an open-label, pragmatic design, we randomly assigned patients with established atherosclerotic cardiovascular disease to a strategy of 81 mg or 325 mg of aspirin per day. The primary effectiveness outcome was a composite of death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke, assessed in a time-to-event analysis. The primary safety outcome was hospitalization for major bleeding, also assessed in a time-to-event analysis. RESULTS: A total of 15,076 patients were followed for a median of 26.2 months (interquartile range [IQR], 19.0 to 34.9). Before randomization, 13,537 (96.0% of those with available information on previous aspirin use) were already taking aspirin, and 85.3% of these patients were previously taking 81 mg of daily aspirin. Death, hospitalization for myocardial infarction, or hospitalization for stroke occurred in 590 patients (estimated percentage, 7.28%) in the 81-mg group and 569 patients (estimated percentage, 7.51%) in the 325-mg group (hazard ratio, 1.02; 95% confidence interval [CI], 0.91 to 1.14). Hospitalization for major bleeding occurred in 53 patients (estimated percentage, 0.63%) in the 81-mg group and 44 patients (estimated percentage, 0.60%) in the 325-mg group (hazard ratio, 1.18; 95% CI, 0.79 to 1.77). Patients assigned to 325 mg had a higher incidence of dose switching than those assigned to 81 mg (41.6% vs. 7.1%) and fewer median days of exposure to the assigned dose (434 days [IQR, 139 to 737] vs. 650 days [IQR, 415 to 922]). CONCLUSIONS: In this pragmatic trial involving patients with established cardiovascular disease, there was substantial dose switching to 81 mg of daily aspirin and no significant differences in cardiovascular events or major bleeding between patients assigned to 81 mg and those assigned to 325 mg of aspirin daily. (Funded by the Patient-Centered Outcomes Research Institute; ADAPTABLE ClinicalTrials.gov number, NCT02697916.).

Background Type 2 diabetes mellitus (DM) is one of the most common comorbidities among patients with heart failure (HF) with reduced ejection fraction (HFrEF). There are limited data regarding efficacy of hybrid comprehensive telerehabilitation (HCTR) on cardiopulmonary exercise capacity in patients with HFrEF with versus those without diabetes. Aim The aim of the present study was to analyze effects of 9-week HCTR in comparison to usual care on parameters of cardiopulmonary exercise capacity in HF patients according to history of DM. Methods Clinically stable HF patients with left ventricular ejection fraction [LVEF] Results CPET was performed in 385 patients assigned to HCTR group: 129 (33.5%) had DM (HCTR-DM group) and 256 patients (66.5%) did not have DM (HCTR-nonDM group). Among 397 patients assigned to UC group who had CPET: 137 (34.5%) had DM (UC-DM group) and 260 patients (65.5%) did not have DM (UC-nonDM group). Among DM patients, differences in cardiopulmonary parameters from baseline to 9 weeks remained similar among HCTR and UC patients. In contrast, among patients without DM, HCTR was associated with greater 9-week changes than UC in exercise time, which resulted in a statistically significant interaction between patients with and without DM: difference in changes in exercise time between HCTR versus UC was 12.0 s [95% CI − 15.1, 39.1 s] in DM and 43.1 s [95% CI 24.0, 63.0 s] in non-DM, interaction p-value = 0.016. Furthermore, statistically significant differences in the effect of HCTR versus UC between DM and non-DM were observed in ventilation at rest: − 0.34 l/min [95% CI − 1.60, 0.91 l/min] in DM and 0.83 l/min [95% CI − 0.06, 1.73 l/min] in non-DM, interaction p value = 0.0496 and in VE/VCO2 slope: 1.52 [95% CI − 1.55, 4.59] for DM vs. − 1.44 [95% CI − 3.64, 0.77] for non-DM, interaction p value = 0.044. Conclusions The benefits of hybrid comprehensive telerehabilitation versus usual care on the improvement of physical performance, ventilatory profile and gas exchange parameters were more pronounced in patients with HFrEF without DM as compared to patients with DM. Trial registration: ClinicalTrials.gov Identifier: NCT02523560. Registered 3rd August 2015. https://clinicaltrials.gov/ct2/show/NCT02523560?term=NCT02523560&draw=2&rank=1. Other Study ID Numbers: STRATEGME1/233547/13/NCBR/2015

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The National Centre for Research and Development, Warsaw, Poland. Background. Cardiac rehabilitation is a component of heart failure (HF) management but its effect on ventricular arrhythmias is not well recognized. Purpose. We analyzed the antiarrhythmic effect of a 9-week hybrid cardiac telerehabilitation (HCTR) and its influence on long term cardiovascular mortality in HF patients taken from the TELEREH-HF trial. Methods. We evaluated the presence of non-sustained ventricular tachycardia (nsVT) and frequent premature ventricular complexes ≥10 beats/hour (PVCs ≥10) with 24-hour ECG monitoring at the baseline and after 9-week HCTR or usual care (UC) of 773 HF patients (NYHA I-III, LVEF ≤ 40%). Results. Among 143 patients with nsVT, arrhythmia subsided in 30.8% after HCTR, similarly among 165 patients randomized to UC who had nsVT 34.5% did not show them after 9 weeks (p = 0.481). There was no significant difference in the decrease in PVC ≥10 over 9 weeks between randomization arms (14.9% vs. 17.8%, respectively p = 0.410). Functional response for HCTR (Δ peak oxygen consumption [pVO2] in cardiopulmonary exercise test >2.0 ml/kg/min) did not affect occurrence of arrhythmias. The multivariable analysis of the entire population did not identify HCTR as an independent factor determining improvement in terms of nsVT or PVCs >10. However, only in the HCTR group, the achievement of the antiarrhythmic effect significantly reduced the cardiovascular mortality in 2 years follow-up (Logrank p = 0.0009) (Figure). Conclusions. Significant improvement in physical capacity after 9 weeks of HCTR did not correlate with the antiarrhythmic effect in terms of incidence of nsVT or PVCs ≥10. An antiarrhythmic effect after the 9-week HCTR affected long term cardiovascular mortality in HF patients. Abstract Figure

If the decision is allowed to stand, it will have major implications for pharmaceutical patents and biomedical innovation.

Background Extended elevations of non–high-density lipoprotein cholesterol (non–HDL-C) across a lifespan are associated with increased risk of cardiovascular disease (CVD). However, optimal testing intervals to identify individuals with high lipid-related CVD risk are unknown. Objectives This study determined the extent to which lipid levels in young adulthood predict future lipid trajectories and associated long-term CVD risk. Methods A sample of 2,516 Framingham Offspring study participants 25 to 40 years of age free of CVD and diabetes had their non–HDL-C progression modeled over 8 study examinations (mean follow-up 32.6 years) using group-based methods. CVD risk based on 25 to 30 years of follow-up was evaluated using Kaplan-Meier analyses for those with mean non–HDL-C ≥160 mg/dl (“high”) and Results The trajectories of the lipid levels were generally stable over the 30-year life course; mean non–HDL-C measured in young adulthood were highly predictive of levels later in life. Individuals could be reliably assigned to high and low non–HDL-C groups based on 2 measurements collected between 25 to 40 years of age. Overall, 80% of those with non–HDL-C ≥160 mg/dl at the first 2 exams remained in the high group on subsequent 25-year testing, whereas 88% of those with non–HDL-C Conclusions Most adults with elevated non–HDL-C early in life continue to have high non–HDL-C over their life course, leading to significantly increased risk of CVD. The results demonstrate that early lipid monitoring before 40 years of age would identify a majority of those with a high likelihood for lifetime elevated lipid levels who also have a high long-term risk for CVD. This information could facilitate informed patient–provider discussion about the potential benefits of preventive lipid-lowering efforts during the early midlife period.

When comparing performances of two risk prediction models, several metrics exist to quantify prognostic improvement, including the change in the area under the Receiver Operating Characteristic curve, the Integrated Discrimination Improvement, the Net Reclassification Index at event rate, the change in Standardized Net Benefit, the change in Brier score, and the change in scaled Brier score. We explore the behavior and interrelationships between these metrics under multivariate normality in nested and nonnested model comparisons. We demonstrate that, within the framework of linear discriminant analysis, all six statistics are functions of squared Mahalanobis distance, a robust metric that properly measures discrimination by quantifying the separation between the risk scores of events and nonevents. These relationships are important for overall interpretability and clinical usefulness. Through simulation, we demonstrate that the performance of the theoretical estimators under normality is comparable or superior to empirical estimation methods typically used by investigators. In particular, the theoretical estimators for the Net Reclassification Index and the change in Standardized Net Benefit exhibit less variability in their estimates as compared to their empirically estimated counterparts. Finally, we explore how these metrics behave with potentially nonnormal data by applying these methods in a practical example based on the sex-specific cardiovascular disease risk models from the Framingham Heart Study. Our findings aim to give greater insight into the behavior of these measures and the connections existing among them and to provide additional estimation methods with less variability for the Net Reclassification Index and the change in Standardized Net Benefit.

Supplemental Digital Content is available in the text., Background: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors—specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking—with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age. Methods: Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non–high-density lipoprotein cholesterol (non–HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed. Results: Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non–HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non–HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to

The last two decades have witnessed an explosion in research focused on the development and assessment of novel biomarkers for improved prognosis of diseases. As a result, best practice standards guiding biomarker research have undergone extensive development. Currently, there is great interest in the promise of biomarkers to enhance research efforts and clinical practice in the setting of chronic kidney disease, acute kidney injury, and glomerular disease. However, some have questioned whether biomarkers currently add value to the clinical practice of nephrology. The current state of the art pertaining to statistical analyses regarding the use of such measures is critical. In December 2014, the National Institute of Diabetes and Digestive and Kidney Diseases convened a meeting, "Toward Building Better Biomarker Statistical Methodology," with the goals of summarizing the current best practice recommendations and articulating new directions for methodological research. This report summarizes its conclusions and describes areas that need attention. Suggestions are made regarding metrics that should be commonly reported. We outline the methodological issues related to traditional metrics and considerations in prognostic modeling, including discrimination and case mix, calibration, validation, and cost-benefit analysis. We highlight the approach to improved risk communication and the value of graphical displays. Finally, we address some "new frontiers" in prognostic biomarker research, including the competing risk framework, the use of longitudinal biomarkers, and analyses in distributed research networks.

Balanced representation learning methods have been applied successfully to counterfactual inference from observational data. However, approaches that account for survival outcomes are relatively limited. Survival data are frequently encountered across diverse medical applications, i.e., drug development, risk profiling, and clinical trials, and such data are also relevant in fields like manufacturing (e.g., for equipment monitoring). When the outcome of interest is a time-to-event, special precautions for handling censored events need to be taken, as ignoring censored outcomes may lead to biased estimates. We propose a theoretically grounded unified framework for counterfactual inference applicable to survival outcomes. Further, we formulate a nonparametric hazard ratio metric for evaluating average and individualized treatment effects. Experimental results on real-world and semi-synthetic datasets, the latter of which we introduce, demonstrate that the proposed approach significantly outperforms competitive alternatives in both survival-outcome prediction and treatment-effect estimation., Accepted at ACM Conference on Health, Inference, and Learning (ACM CHIL 2021). Code at https://github.com/paidamoyo/counterfactual_survival_analysis

IMPORTANCE: Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making, and novel methods hold promise for using existing data to generate additional insights. OBJECTIVE: To evaluate whether contemporary machine learning methods can facilitate risk prediction by including a larger number of variables and identifying complex relationships between predictors and outcomes. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used the American College of Cardiology Chest Pain-MI Registry to identify all AMI hospitalizations between January 1, 2011, and December 31, 2016. Data analysis was performed from February 1, 2018, to October 22, 2020. MAIN OUTCOMES AND MEASURES: Three machine learning models were developed and validated to predict in-hospital mortality based on patient comorbidities, medical history, presentation characteristics, and initial laboratory values. Models were developed based on extreme gradient descent boosting (XGBoost, an interpretable model), a neural network, and a meta-classifier model. Their accuracy was compared against the current standard developed using a logistic regression model in a validation sample. RESULTS: A total of 755 402 patients (mean [SD] age, 65 [13] years; 495 202 [65.5%] male) were identified during the study period. In independent validation, 2 machine learning models, gradient descent boosting and meta-classifier (combination including inputs from gradient descent boosting and a neural network), marginally improved discrimination compared with logistic regression (C statistic, 0.90 for best performing machine learning model vs 0.89 for logistic regression). Nearly perfect calibration in independent validation data was found in the XGBoost (slope of predicted to observed events, 1.01; 95% CI, 0.99-1.04) and the meta-classifier model (slope of predicted-to-observed events, 1.01; 95% CI, 0.99-1.02), with more precise classification across the risk spectrum. The XGBoost model reclassified 32 393 of 121 839 individuals (27%) and the meta-classifier model reclassified 30 836 of 121 839 individuals (25%) deemed at moderate to high risk for death in logistic regression as low risk, which were more consistent with the observed event rates. CONCLUSIONS AND RELEVANCE: In this cohort study using a large national registry, none of the tested machine learning models were associated with substantive improvement in the discrimination of in-hospital mortality after AMI, limiting their clinical utility. However, compared with logistic regression, XGBoost and meta-classifier models, but not the neural network, offered improved resolution of risk for high-risk individuals.

Background Heart failure (HF) is a clinical syndrome associated with physical capacity impairment and poor quality of life (QoL). The hybrid comprehensive telerehabilitation (HCTR) consisting of telecare, telerehabilitation and homemonitoring of implantable devices might be an option to improve QoL. Purpose to investigate the influence of HCTR on various facets of QoL in HF pts in comparison to usual care (UC). Methods The present analysis formed part of TELEREH-HF multicenter, randomized trial that enrolled 850 HF pts (NYHA I-III, LVEF≤40%). Patients were randomized 1:1 to HCTR plus UC or UC. Patients underwent either an HCTR (1 week in hospital and 8 weeks at home) or UC with observation. The psychology telecare had a form of supportive psychotherapy via phone. The Short Form 36 Questionnaire was used to assess QoL. Measurements were made before and after intervention/observation. Results HCTR group showed significant improvement in overall QoL, physical domain, and 4 areas of QoL (physical functioning [PF], role functioning related to physical state, general health, vitality). A significant positive change in QoL in UC group was observed in vitality and social functioning. There were significant differences in QoL after intervention/observation between groups. Results showed higher improvement in HCTR for overall QoL, physical domain and 3 areas of QoL (PF, role functioning related to physical state and bodily pain [BP]), Table 1. Conclusion In comparison to UC, HCTR resulted in significant improvement in overall QoL, physical domain and 3 specific areas of QoL: PF, role functioning related to physical state and BP. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Centre for Research and Development, Warsaw, Poland

Background Adherence to treatment guidelines in heart failure (HF) patients (pts) is of major prognostic importance, but thorough implementation of guidelines in routine care remains insufficient. Introducing hybrid comprehensive telerehabilitation (HCTR) consisting of telecare, telerehabilitation and remote monitoring of implantable devices might be an option to improve adherence to recommendation and can affect the prognosis. Purpose to investigate the association of adherence to HCTR with mortality and hospitalization. Methods The present analysis formed part of TELEREH-HF multicenter, randomized trial that enrolled 850 HF pts (NYHA I-III,LVEF≤40%). Patients were randomized 1:1 to HCTR plus usual care or usual care only and followed up for 14 to 26 months. During the first 9 weeks, pts underwent either an HCTR (1 week in hospital and 8 weeks at home) or usual care. This analysis focuses on pts randomized to HCTR. Adherent pts were those who adhered both to the number of training sessions prescribed and to the duration of the prescribed cycle by at least80%; non-adherent pts, were those who adhered Results There were 350 (88.4%) adherent pts, 39 (9.8%) partially adherent pts and 7 (1.8%) non-adherent pts. There were 54 deaths during follow-up in the HCTR arm. Non-adherence or partial adherence was associated with statistically significantly higher risk of cardiovascular (CV) mortality (hazard ratio (HR) = 2.62, p=0.021); all-cause mortality or HF hospitalization (HR=1.71, p=0.038); CV mortality or HF hospitalization (HR=1.89, p=0.014). Conclusion The adherence to HCTR was very high. Adherence to HCTR was associated with improved prognosis for CV mortality. Kaplan-Meier Probability of CV Mortality Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Centre for Research and Development, Warsaw, Poland

Models for predicting the time of a future event are crucial for risk assessment, across a diverse range of applications. Existing time-to-event (survival) models have focused primarily on preserving pairwise ordering of estimated event times, or relative risk. Model calibration is relatively under explored, despite its critical importance in time-to-event applications. We present a survival function estimator for probabilistic predictions in time-to-event models, based on a neural network model for draws from the distribution of event times, without explicit assumptions on the form of the distribution. This is done like in adversarial learning, but we achieve learning without a discriminator or adversarial objective. The proposed estimator can be used in practice as a means of estimating and comparing conditional survival distributions, while accounting for the predictive uncertainty of probabilistic models. Extensive experiments show that the proposed model outperforms existing approaches, trained both with and without adversarial learning, in terms of both calibration and concentration of time-to-event distributions.

Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneous treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made based only on an overall average treatment effect. We distinguished two categories of predictive HTE approaches (a “risk modeling” and an “effect modeling” approach) and developed four sets of guidance statements: 1) criteria to determine when risk modeling approaches are likely to identify clinically meaningful HTE; 2) methodological aspects of risk modeling methods; 3) considerations for translation to clinical practice; and 4) considerations and caveats in the use of effect modeling approaches. We also discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation; and discusses related analytic considerations, caveats, and reservations.

In a recent decision that stunned many in the legal and pharmaceutical communities, the chief judge of the U.S. District Court of the District of Nevada in Las Vegas, Judge Miranda Du, struck down 6 key method-of-use patents for the omega-3 fatty acid preparation, icosapent ethyl (Vascepa®). If this judgment is allowed to stand on appeal in Amarin Pharma, Inc., v. Hikma Pharmaceuticals USA, Inc., et al., it will have major implications not only for the patent protection of this drug but for pharmaceutical patents and biomedical innovation more generally. We review the background of this judicial opinion and suggest the decision should be reversed on appeal. The Judge based her opinion on her conclusion that the patents, at the time of the invention, would have been obvious to a person having ordinary skill in the art (35 U.S.C. § 103). As we will show, a key piece of the prior art, which was central to this case, included an incorrect conclusion based on a common statistical error. Our central argument is that prior art that is scientifically incorrect should not be an acceptable basis for invalidating patents as obvious.

IMPORTANCE: The extent to which levels of high-sensitivity C-reactive protein (hs-CRP), a known marker of increased cardiovascular risk, are elevated and are associated with standard cardiovascular risk factors in patients with a history of myocardial infarction (MI) is unknown. OBJECTIVES: To determine the pattern and determinants of the distribution of hs-CRP in those with a prior MI in the United States using a nationally representative sample. DESIGN AND PARTICIPANTS: Adults with hs-CRP data in the National Health and Nutrition Examination Surveys from 1999–2010. RESULTS: Among 1296 individuals in our cohort, the median age was 65 years and the median hs-CRP level was 2.69 mg/L, measured an average of 7.1 years after the MI. Among these patients, 22% had hs-CRP levels of

Supplemental Digital Content is available in the text., Background: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction. Methods: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non–HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events). Results: ApoB, LDL-C, and non–HDL-C were highly correlated (r>0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non–HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non–HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non–HDL-C did not further improve discrimination. Conclusions: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C.

In clinical trials, placebo response can affect the inference about efficacy of the studied treatment. It is important to have a robust way to classify trial subjects with respect to their response to placebo. Simple, criterion-based classification may lead to classification error and bias the inference. The uncertainty about placebo response characteristic has to be factored into the treatment effect estimation. We propose a novel approach that views the placebo response as a latent characteristic and the study sample as an unlabeled mixture of “placebo responders” and “placebo nonresponders.” The likelihood-based methodology is used to estimate the treatment effect corrected for placebo response as defined within sequential parallel comparison design.

IMPORTANCE: Guidelines recommend exercise training as a component of heart failure management. There are large disparities in access to rehabilitation, and introducing hybrid comprehensive telerehabilitation (HCTR) consisting of remote monitoring of training at patients’ homes might be an appealing alternative. OBJECTIVE: To assess whether potential improvements in quality-of-life outcomes after a 9-week HCTR intervention in patients with heart failure translate into improvement in clinical outcomes during extended 12 to 24 months of follow-up, compared with usual care. DESIGN, SETTING, AND PARTICIPANTS: The Telerehabilitation in Heart Failure Patients (TELEREH-HF) trial is a multicenter, prospective, open-label, parallel-group randomized clinical trial that enrolled 850 patients with heart failure up to 6 months after a cardiovascular hospitalization with New York Heart Association levels I, II, or III and left ventricular ejection fraction of 40% or less. Patients from 5 centers in Poland were randomized 1:1 to HCTR plus usual care or usual care only and followed up for 14 to 26 months after randomization. INTERVENTIONS: During the first 9 weeks, patients underwent either an HCTR program (1 week in hospital and 8 weeks at home) or usual care with observation. The HCTR intervention encompassed telecare, telerehabilitation, and remote monitoring of implantable devices. No intervention occurred in the remaining study period. MAIN OUTCOMES AND MEASURES: The percentage of days alive and out of the hospital from randomization through the end of follow-up at 14 to 26 months. RESULTS: A total of 850 patients were enrolled, with 425 randomized to the HCTR group (377 male patients [88.7%]; mean [SD] age, 62.6 [10.8] years) and 425 randomized to usual care (376 male patients [88.5%]; mean [SD] age, 62.2 [10.2] years). The HCTR intervention did not extend the percentage of days alive and out of the hospital. The mean (SD) days were 91.9 (19.3) days in the HCTR group vs 92.8 (18.3) days in the usual-care group, with the probability that HCTR extends days alive and out of the hospital equal to 0.49 (95% CI, 0.46-0.53; P = .74) vs usual care. During follow-up, 54 patients died in the HCTR arm and 52 in the usual-care arm, with mortality rates at 26 months of 12.5% vs 12.4%, respectively (hazard ratio, 1.03 [95% CI, 0.70-1.51]). There were also no differences in hospitalization rates (hazard ratio, 0.94 [95% CI, 0.79-1.13]). The HCTR intervention was effective at 9 weeks, significantly improving peak oxygen consumption (0.95 [95% CI, 0.65-1.26] mL/kg/min vs 0.00 [95% CI, −0.31 to 0.30] mL/kg/min; P