BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763–0.809) in female and 0.757 (0.727–0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81–1.16) and 0.94 (0.81–1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD– and heart failure–specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004–0.005] and 0.005 [0.004–0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84–1.20] versus 1.39 [1.14–1.65]; P =0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

The prevalence of obesity has increased globally over the last 2 decades. Although the body mass index has been a convenient and simple index of obesity at the population level, studies have shown that obesity defined by body mass index alone is a remarkably heterogeneous condition with varying cardiovascular and metabolic manifestations across individuals. Adipose tissue is an exquisitely active metabolic organ engaged in cross-talk between various systems; perturbation of adipose tissue results in a pathological response to positive caloric balance in susceptible individuals that directly and indirectly contributes to cardiovascular and metabolic disease. Inadequate subcutaneous adipose tissue expansion in the face of dietary triglycerides leads to visceral and ectopic fat deposition, inflammatory/adipokine dysregulation, and insulin resistance. Conversely, preferential fat storage in the lower body depot may act as a metabolic buffer and protect other tissues from lipotoxicity caused by lipid overflow and ectopic fat. Translational, epidemiological, and clinical studies over the past 30 years have clearly demonstrated a strong link between visceral and ectopic fat and the development of a clinical syndrome characterized by atherogenic dyslipidemia, hyperinsulinemia/glucose intolerance, hypertension, atherosclerosis, and adverse cardiac remodeling/heart failure. This relationship is even more nuanced when clinical entities such as metabolically healthy obesity phenotype and the obesity paradox are considered. Although it is clear that the accumulation of visceral/ectopic fat is a major contributor to cardiovascular and metabolic risk above and beyond the body mass index, implementation of fat distribution assessment into clinical practice remains a challenge. Anthropometric indexes of obesity are easily implemented, but newer imaging-based methods offer improved sensitivity and specificity for measuring specific depots. Lifestyle, pharmacological, and surgical interventions allow a multidisciplinary approach to overweight/obesity that may improve outcomes and align with a public health message to combat the growing epidemic of obesity worldwide and to build healthier lives free of cardiovascular diseases.

Weight loss induced by glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) and dual glucagon‐like peptide‐1 receptor (GLP‐1R)/glucose‐dependent insulinotropic polypeptide receptor agonists is coming closer to the magnitudes achieved with surgery. However, with greater weight loss there is concern about potential side effects on muscle quantity (mass), health and function. There is heterogeneity in the reported effects of GLP‐1‐based therapies on lean mass changes in clinical trials: in some studies, reductions in lean mass range between 40% and 60% as a proportion of total weight lost, while other studies show lean mass reductions of approximately 15% or less of total weight lost. There are several potential reasons underlying this heterogeneity, including population, drug‐specific/molecular, and comorbidity effects. Furthermore, changes in lean mass may not always reflect changes in muscle mass as the former measure includes not only muscle but also organs, bone, fluids, and water in fat tissue. Based on contemporary evidence with the addition of magnetic resonance imaging‐based studies, skeletal muscle changes with GLP‐1RA treatments appear to be adaptive: reductions in muscle volume seem to be commensurate with what is expected given ageing, disease status, and weight loss achieved, and the improvement in insulin sensitivity and muscle fat infiltration likely contributes to an adaptive process with improved muscle quality, lowering the probability for loss in strength and function. Nevertheless, factors such as older age and severity of disease may influence the selection of appropriate candidates for these therapies due to risk of sarcopenia. To further improve muscle health during weight loss, several pharmacological treatments to maintain or improve muscle mass designed in combination with GLP‐1‐based therapies are under development. Future research on GLP‐1‐based and other therapies designed for weight loss should focus on more accurate and meaningful assessments of muscle mass, composition, as well as function, mobility or strength, to better define their impact on muscle health for the substantial number of patients who will likely be taking these medications well into the future.

Summary: Objective: To review the efficacy, safety, and clinical applicability of liraglutide for weight management from phase III clinical trials.Methods: A search of the English language literature was performed using PubMed search terms: “liraglutide”, “glucagon‐like peptide‐1 receptor agonist”, and “randomized clinical trial”. Articles and bibliographies relevant to the subject were reviewed and additional references known to the authors were included.Results: Five randomized, placebo‐controlled trials of liraglutide for weight management were identified. In addition to recommended diet and physical activity, liraglutide consistently resulted in a 4 to 6 kg weight loss, with a greater proportion of patients achieving at least 5 and 10% weight loss compared with placebo. The most common adverse effects were gastrointestinal and primarily occurred early in the treatment course. Comparative data suggest that weight loss with liraglutide is greater than that seen with orlistat or lorcaserin, but slightly less that seen with phentermine/topiramate. Liraglutide 1.8 mg was recently shown to have cardiovascular benefit in a large outcomes trial; applicability of these results for the 3.0 mg formulation in a more diverse weight loss population at high cardiovascular risk is not currently known. Barriers to real‐world clinical use as a first‐line agent include gastrointestinal side effects, high cost, and need for injection.Conclusions: Liraglutide helps to induce and sustain weight loss in patients with obesity. Its efficacy is comparable to other available agents but it offers the unique benefit of improved glycemic control. Additional studies are needed to determine its long term efficacy and safety profile.

Background: Obesity may contribute to adverse outcomes in coronavirus disease 2019 (COVID-19). However, studies of large, broadly generalizable patient populations are lacking, and the effect of body mass index (BMI) on COVID-19 outcomes— particularly in younger adults—remains uncertain. Methods: We analyzed data from patients hospitalized with COVID-19 at 88 US hospitals enrolled in the American Heart Association’s COVID-19 Cardiovascular Disease Registry with data collection through July 22, 2020. BMI was stratified by World Health Organization obesity class, with normal weight prespecified as the reference group. Results: Obesity, and, in particular, class III obesity, was overrepresented in the registry in comparison with the US population, with the largest differences among adults ≤50 years. Among 7606 patients, in-hospital death or mechanical ventilation occurred in 2109 (27.7%), in-hospital death in 1302 (17.1%), and mechanical ventilation in 1602 (21.1%). After multivariable adjustment, classes I to III obesity were associated with higher risks of in-hospital death or mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09–1.51], 1.57 [1.29–1.91], 1.80 [1.47–2.20], respectively), and class III obesity was associated with a higher risk of in-hospital death (hazard ratio, 1.26 [95% CI, 1.00–1.58]). Overweight and class I to III obese individuals were at higher risk for mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09–1.51], 1.54 [1.29–1.84], 1.88 [1.52–2.32], and 2.08 [1.68–2.58], respectively). Significant BMI by age interactions were seen for all primary end points ( P -interaction70 years. Severe obesity (BMI ≥40 kg/m ² ) was associated with an increased risk of in-hospital death only in those ≤50 years (hazard ratio, 1.36 [1.01–1.84]). In adjusted analyses, higher BMI was associated with dialysis initiation and with venous thromboembolism but not with major adverse cardiac events. Conclusions: Obese patients are more likely to be hospitalized with COVID-19, and are at higher risk of in-hospital death or mechanical ventilation, in particular, if young (age ≤50 years). Obese patients are also at higher risk for venous thromboembolism and dialysis. These observations support clear public health messaging and rigorous adherence to COVID-19 prevention strategies in all obese individuals regardless of age.