@article {7356, title = {Relationship Between Physical Activity, Body Mass Index, and Risk of Heart Failure.}, journal = {J Am Coll Cardiol}, volume = {69}, year = {2017}, month = {2017 Mar 07}, pages = {1129-1142}, abstract = {

BACKGROUND: Lower leisure-time physical activity (LTPA) and higher body mass index (BMI) are independently associated with risk of heart failure (HF). However, it is unclear if this relationship is consistent for both heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF).

OBJECTIVES: This study sought to quantify dose-response associations between LTPA, BMI, and the risk of different HF subtypes.

METHODS: Individual-level data from 3 cohort studies (WHI [Women{\textquoteright}s Health Initiative], MESA [Multi-Ethnic Study of Atherosclerosis], and CHS [Cardiovascular Health Study]) were pooled and participants were stratified into guideline-recommended categories of LTPA and BMI. Associations between LTPA, BMI, and risk of overall HF, HFpEF (ejection fraction~>=45\%), and HFrEF (ejection fraction~<45\%) were assessed by using multivariable adjusted Cox models and restricted cubic splines.

RESULTS: The study included 51,451 participants with 3,180 HF events (1,252 HFpEF, 914 HFrEF, and 1,014 unclassified HF). In the adjusted analysis, there was a dose-dependent association between higher LTPA levels, lower BMI, and overall~HF risk. Among HF subtypes, LTPA in any dose range was not associated with HFrEF risk. In contrast, lower levels of LTPA (<500 MET-min/week) were not associated with HFpEF risk, and dose-dependent associations with lower HFpEF risk were observed at higher levels. Compared with no LTPA, higher than twice the guideline-recommended minimum LTPA levels (>1,000 MET-min/week) were associated with an 19\% lower risk of HFpEF (hazard ratio: 0.81; 95\% confidence interval: 0.68 to 0.97). The dose-response relationship for BMI with HFpEF risk was also more consistent than with HFrEF risk, such that increasing BMI above the normal range (>=25 kg/m(2)) was associated with a greater increase in risk of HFpEF than HFrEF.

CONCLUSIONS: Our study findings show strong, dose-dependent associations between LTPA levels, BMI, and risk~of~overall HF. Among HF subtypes, higher LTPA levels and lower BMI were more consistently associated with~lower~risk of HFpEF compared with HFrEF.

}, issn = {1558-3597}, doi = {10.1016/j.jacc.2016.11.081}, author = {Pandey, Ambarish and LaMonte, Michael and Klein, Liviu and Ayers, Colby and Psaty, Bruce M and Eaton, Charles B and Allen, Norrina B and de Lemos, James A and Carnethon, Mercedes and Greenland, Philip and Berry, Jarett D} } @article {7685, title = {Sex and Race Differences in Lifetime Risk of Heart Failure With Preserved Ejection Fraction and Heart Failure With Reduced Ejection Fraction.}, journal = {Circulation}, volume = {137}, year = {2018}, month = {2018 Apr 24}, pages = {1814-1823}, abstract = {

BACKGROUND: Lifetime risk of heart failure has been estimated to range from 20\% to 46\% in diverse sex and race groups. However, lifetime risk estimates for the 2 HF phenotypes, HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF), are not known.

METHODS: Participant-level data from 2 large prospective cohort studies, the CHS (Cardiovascular Health Study) and MESA (Multiethnic Study of Atherosclerosis), were pooled, excluding individuals with prevalent HF at baseline. Remaining lifetime risk estimates for HFpEF (EF >=45\%) and HFrEF (EF <45\%) were determined at different index ages with the use of a modified Kaplan-Meier method with mortality and the other HF subtype as competing risks.

RESULTS: We included 12 417 participants >45 years of age (22.2\% blacks, 44.8\% men) who were followed up for median duration of 11.6 years with 2178 overall incident HF events with 561 HFrEF events and 726 HFpEF events. At the index age of 45 years, the lifetime risk for any HF through 90 years of age was higher in men than women (27.4\% versus 23.8\%). Among HF subtypes, the lifetime risk for HFrEF was higher in men than women (10.6\% versus 5.8\%). In contrast, the lifetime risk for HFpEF was similar in men and women. In race-stratified analyses, lifetime risk for overall HF was higher in nonblacks than blacks (25.9\% versus 22.4\%). Among HF subtypes, the lifetime risk for HFpEF was higher in nonblacks than blacks (11.2\% versus 7.7\%), whereas that for HFrEF was similar across the 2 groups. Among participants with antecedent myocardial infarction before HF diagnosis, the remaining lifetime risks for HFpEF and HFrEF were up to 2.5-fold and 4-fold higher, respectively, compared with those without antecedent myocardial infarction.

CONCLUSIONS: Lifetime risks for HFpEF and HFrEF vary by sex, race, and history of antecedent myocardial infarction. These insights into the distribution of HF risk and its subtypes could inform the development of targeted strategies to improve population-level HF prevention and control.

}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.117.031622}, author = {Pandey, Ambarish and Omar, Wally and Ayers, Colby and LaMonte, Michael and Klein, Liviu and Allen, Norrina B and Kuller, Lewis H and Greenland, Philip and Eaton, Charles B and Gottdiener, John S and Lloyd-Jones, Donald M and Berry, Jarett D} } @article {8626, title = {Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index.}, journal = {JAMA Netw Open}, volume = {3}, year = {2020}, month = {2020 10 01}, pages = {e2023242}, abstract = {

Importance: Obesity is a global health challenge and a risk factor for atherosclerotic cardiovascular disease (ASVCD). Performance of the pooled cohort equations (PCE) for ASCVD risk by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is unknown.

Objective: To assess performance of the PCE across clinical BMI categories.

Design, Setting, and Participants: This cohort study used pooled individual-level data from 8 community-based, prospective, longitudinal cohort studies with 10-year ASCVD event follow-up from 1996 to 2016. We included all adults ages 40 to 79 years without baseline ASCVD or statin use, resulting in a sample size of 37 311 participants. Data were analyzed from August 2017 to July 2020.

Exposures: Participant BMI category: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), mild obesity (30 to <35), and moderate to severe obesity (>=35).

Main Outcomes and Measures: Discrimination (Harrell C statistic) and calibration (Nam-D{\textquoteright}Agostino χ2 goodness-of-fit test) of the PCE across BMI categories. Improvement in discrimination and net reclassification with addition of BMI, waist circumference, and high-sensitivity C-reactive protein (hsCRP) to the PCE.

Results: Among 37 311 participants (mean [SD] age, 58.6 [11.8] years; 21 897 [58.7\%] women), 380 604 person-years of follow-up were conducted. Mean (SD) baseline BMI was 29.0 (6.2), and 360 individuals (1.0\%) were in the underweight category, 9937 individuals (26.6\%) were in the normal weight category, 13 601 individuals (36.4\%) were in the overweight category, 7783 individuals (20.9\%) were in the mild obesity category, and 5630 individuals (15.1\%) were in the moderate to severe obesity category. Median (interquartile range [IQR]) 10-year estimated ASCVD risk was 7.1\% (2.5\%-15.4\%), and 3709 individuals (9.9\%) developed ASCVD over a median (IQR) 10.8 [8.5-12.6] years. The PCE overestimated ASCVD risk in the overall cohort (estimated/observed [E/O] risk ratio, 1.22; 95\% CI, 1.18-1.26) and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity (E/O risk ratio, 1.36; 95\% CI, 1.25-1.47) and among those with the highest estimated ASCVD risk >=20\%. The PCE C statistic overall was 0.760 (95\% CI, 0.753-0.767), with lower discrimination in the moderate or severe obesity group (C statistic, 0.742; 95\% CI, 0.721-0.763) compared with the normal-range BMI group (C statistic, 0.785; 95\% CI, 0.772-0.798). Waist circumference (hazard ratio, 1.07 per 1-SD increase; 95\% CI, 1.03-1.11) and hsCRP (hazard ratio, 1.07 per 1-SD increase; 95\% CI, 1.05-1.09), but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance (C statistic, 0.760; 95\% CI, 0.753-0.767) with or without added metrics.

Conclusions and Relevance: These findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.

}, keywords = {Adult, Aged, Body Mass Index, Cardiovascular Diseases, Cohort Studies, Correlation of Data, Female, Humans, Longitudinal Studies, Male, Middle Aged, Proportional Hazards Models, Prospective Studies, Risk Assessment, Risk Factors}, issn = {2574-3805}, doi = {10.1001/jamanetworkopen.2020.23242}, author = {Khera, Rohan and Pandey, Ambarish and Ayers, Colby R and Carnethon, Mercedes R and Greenland, Philip and Ndumele, Chiadi E and Nambi, Vijay and Seliger, Stephen L and Chaves, Paulo H M and Safford, Monika M and Cushman, Mary and Xanthakis, Vanessa and Vasan, Ramachandran S and Mentz, Robert J and Correa, Adolfo and Lloyd-Jones, Donald M and Berry, Jarett D and de Lemos, James A and Neeland, Ian J} } @article {8788, title = {Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels.}, journal = {JAMA Cardiol}, volume = {6}, year = {2021}, month = {2021 Jun 01}, pages = {690-696}, abstract = {

Importance: The American Heart Association/American College of Cardiology pooled cohort equations (PCEs) are used for predicting 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Pooled cohort equation risk prediction capabilities across self-reported leisure-time physical activity (LTPA) levels and the change in model performance with addition of LTPA to the PCE are unclear.

Objective: To evaluate PCE risk prediction performance across self-reported LTPA levels and the change in model performance by adding LTPA to the existing PCE model.

Design, Setting, and Participants: Individual-level pooling of data from 3 longitudinal cohort studies-Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Cardiovascular Health Study-was performed. A total of 18 824 participants were stratified into 4 groups based on self-reported LTPA levels: inactive (0 metabolic equivalent of task [MET]-min/wk), less than guideline-recommended (<500 MET-min/wk), guideline-recommended (500-1000 MET-min/week), and greater than guideline-recommended (>1000 MET-min/wk). Pooled cohort equation risk discrimination was studied using the C statistic and reclassification capabilities were studied using the Greenwood Nam-D{\textquoteright}Agostino χ2 goodness-of-fit test. Change in risk discrimination and reclassification on adding LTPA to PCEs was evaluated using change in C statistic, integrated discrimination index, and categorical net reclassification index.

Main Outcomes and Measures: Adjudicated ASCVD events during 10-year follow-up.

Results: Among 18 824 participants studied, 10 302 were women (54.7\%); mean (SD) age was 57.6 (8.2) years. A total of 5868 participants (31.2\%) were inactive, 3849 (20.4\%) had less than guideline-recommended LTPA, 3372 (17.9\%) had guideline-recommended LTPA, and 5735 (30.5\%) had greater than guideline-recommended LTPA level. Higher LTPA levels were associated with a lower risk of ASCVD after adjustment for risk factors (hazard ratio [HR] per 1-SD higher LTPA, 0.91; 95\% CI, 0.86-0.96). Across LTPA groups, PCE risk discrimination (C statistic, 0.76-0.78) and risk calibration (all χ2 P > .10) was similar. Addition of LTPA to the PCE model resulted in no significant change in the C statistic (0.0005; 95\% CI, -0.0004 to 0.0015; P = .28) and categorical net reclassification index (-0.003; 95\% CI, -0.010 to 0.010; P = .95), but a minimal improvement in the integrated discrimination index (0.0008; 95\% CI, 0.0002-0.0013; P = .005) was observed. Similar results were noted when cohort-specific coefficients were used for creating the baseline model.

Conclusions and Relevance: Higher self-reported LTPA levels appear to be associated with lower ASCVD risk and increasing LTPA promotes cardiovascular wellness. These findings suggest the American Heart Association/American College of Cardiology PCEs are accurate at estimating the probability of 10-year ASCVD risk regardless of LTPA level. The addition of self-reported LTPA to PCEs does not appear to be associated with improvement in risk prediction model performance.

}, issn = {2380-6591}, doi = {10.1001/jamacardio.2021.0948}, author = {Pandey, Ambarish and Mehta, Anurag and Paluch, Amanda and Ning, Hongyan and Carnethon, Mercedes R and Allen, Norrina B and Michos, Erin D and Berry, Jarett D and Lloyd-Jones, Donald M and Wilkins, John T} } @article {8976, title = {Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts.}, journal = {Circulation}, volume = {145}, year = {2022}, month = {2022 01 25}, pages = {268-278}, abstract = {

BACKGROUND: Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established.

METHODS: Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI>=30 kg/m), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes.

RESULTS: The study included 10 387 participants (52.9\% ARIC; 25.1\% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3\%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95\% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI ( interaction=0.04) and WC ( interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95\% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8\%, 29.9\%, and 13.7\%, respectively) versus those without diabetes (<=1\% for each).

CONCLUSIONS: Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes.

}, keywords = {Aged, Cohort Studies, Diabetes Mellitus, Female, Heart Failure, Humans, Male, National Heart, Lung, and Blood Institute (U.S.), Obesity, Risk Factors, United States}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.121.055830}, author = {Patel, Kershaw V and Segar, Matthew W and Lavie, Carl J and Kondamudi, Nitin and Neeland, Ian J and Almandoz, Jaime P and Martin, Corby K and Carbone, Salvatore and Butler, Javed and Powell-Wiley, Tiffany M and Pandey, Ambarish} } @article {9745, title = {Development and validation of a machine learning-based approach to identify high-risk diabetic cardiomyopathy phenotype.}, journal = {Eur J Heart Fail}, year = {2024}, month = {2024 Sep 06}, abstract = {

AIMS: Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abnormalities that precede the development of clinical heart failure (HF), is lacking. In this study, we developed and validated a machine learning-based clustering approach to identify the high-risk DbCM phenotype based on echocardiographic and cardiac biomarker parameters.

METHODS AND RESULTS: Among individuals with diabetes from the Atherosclerosis Risk in Communities (ARIC) cohort who were free of cardiovascular disease and other potential aetiologies of cardiomyopathy (training, n = 1199), unsupervised hierarchical clustering was performed using echocardiographic parameters and cardiac biomarkers of neurohormonal stress and chronic myocardial injury (total 25 variables). The high-risk DbCM phenotype was identified based on the incidence of HF on follow-up. A deep neural network (DeepNN) classifier was developed to predict DbCM in the ARIC training cohort and validated in an external community-based cohort (Cardiovascular Health Study [CHS]; n = 802) and an electronic health record (EHR) cohort (n = 5071). Clustering identified three phenogroups in the derivation cohort. Phenogroup-3 (n = 324, 27\% of the cohort) had significantly higher 5-year HF incidence than other phenogroups (12.1\% vs. 4.6\% [phenogroup 2] vs. 3.1\% [phenogroup 1]) and was identified as the high-risk DbCM phenotype. The key echocardiographic predictors of high-risk DbCM phenotype were higher NT-proBNP levels, increased left ventricular mass and left atrial size, and worse diastolic function. In the CHS and University of Texas (UT) Southwestern EHR validation cohorts, the DeepNN classifier identified 16\% and 29\% of participants with DbCM, respectively. Participants with (vs. without) high-risk DbCM phenotype in the external validation cohorts had a significantly higher incidence of HF (hazard ratio [95\% confidence interval] 1.61 [1.18-2.19] in CHS and 1.34 [1.08-1.65] in the UT Southwestern EHR cohort).

CONCLUSION: Machine learning-based techniques may identify 16\% to 29\% of individuals with diabetes as having a high-risk DbCM phenotype who may benefit from more aggressive implementation of HF preventive strategies.

}, issn = {1879-0844}, doi = {10.1002/ejhf.3443}, author = {Segar, Matthew W and Usman, Muhammad Shariq and Patel, Kershaw V and Khan, Muhammad Shahzeb and Butler, Javed and Manjunath, Lakshman and Lam, Carolyn S P and Verma, Subodh and Willett, DuWayne and Kao, David and Januzzi, James L and Pandey, Ambarish} }