Older age, smoking, macroalbuminuria, microalbuminuria, previous MI, diabetes, and glycated hemoglobin predict risk
THURSDAY, Aug. 22, 2024 (HealthDay News) — A study published online Aug. 21 in the Journal of the American Heart Association reveals the major contributors to heart failure risk in American Indians, highlighting the roles of age, smoking, and diabetes.
Irene Martinez-Morata, M.D., M.P.H., from the Columbia University Mailman School of Public Health in New York City, and colleagues developed a parsimonious heart failure risk prediction equation that accounts for relevant risk factors affecting American Indian communities using data from 3,059 participants from the Strong Heart Study (507 of whom developed heart failure). Risk factors for heart failure and heart failure subtypes were identified using progressively adjusted Cox proportional hazards models.
The researchers found that at five and 10 years, predictors of risk included older age (hazard ratios, 1.79 and 1.68, respectively), smoking (hazard ratios, 2.26 and 2.08, respectively), macroalbuminuria (hazard ratios, 8.38 and 5.20, respectively), microalbuminuria (hazard ratios, 2.72 and 1.92, respectively), and previous myocardial infarction (hazard ratios, 6.58 and 3.87, respectively). At 10 and 28 years, these predictors were significant, together with diabetes diagnosis and glycated hemoglobin. At five, 10, and up to 28 years of follow-up, high discrimination performance was achieved (C-index, 0.81, 0.78, and 0.77, respectively). There was variation observed in some associations across heart failure subtypes, but associations for diabetes, albuminuria, and previous myocardial infarction were consistent across subtypes.
“Our proposed model may serve as a relevant tool for early risk detection and prevention of heart failure in American Indian communities and other populations with a high burden of diabetes,” the authors write.
Cancer Risk ID"d for Asian American, NHPI Population
2011 to 2021 Saw Heart Failure-Related Hospitalization Rise in CKD
Machine Learning Model IDs Heart Failure With Reduced Ejection Fraction Using Routine Lab Indicators
Insurance Poses Barrier to Virtual Pulmonary Rehabilitation for COPD
Higher Short-Term Exposure to Pollen Linked to Lower FEV1 in COPD
Emergency Diagnosis Linked to Worse Outcomes for Range of Conditions
Higher Diet Quality Linked to Improved Lung Function in Asthma, COPD
Cognitive, Manual Impairment Tied to Unacceptable Inhaler Technique