Longitudinal modeling of cardiac function to identify trajectories with differential risk of heart failure

Abstract Background Impairments in left ventricular (LV) systolic and diastolic function are common precursors of clinical heart failure (HF) and underlie HF risk. Little data exist regarding trajectories of cardiac function in mid- to late-life, when HF risk is greatest, and the extent to which such trajectories may differentially relate to risk of HF with preserved ejection fraction (HFpEF) or HF with reduced ejection fraction (HFrEF). Purpose To (1) identify multidimensional trajectories of cardiac function from mid- to late-life using serial echocardiographic data, (2) apply the resulting models to predict trajectory membership in a separate sample, and (3) determine associations between assigned trajectory and incident HFpEF and HFrEF. Methods We used a Bayesian nonparametric trajectory approach to jointly model longitudinal measures of LV ejection fraction (LVEF) and E/A ratio among 747 participants in two longitudinal cohort studies (the Atherosclerosis Risk in Communities [ARIC] study and Jackson Heart Study [JHS]) who underwent ≥2 echocardiograms in 2000-04 (mean age 65±5 years), 2011-2013 (age 75±5 years), and 2018-19 (age 81±5 years). Using the trajectories inferred from this modeling, we applied Bayes theorem to assign 4,419 ARIC-only participants to their most likely trajectory using single time-point measures of LVEF and E/A ratio acquired in 2011-2013 (age 75±5 years). These assignments were treated as a categorical variable in subsequent analysis. In ARIC-only participants, we used Cox proportional hazards models adjusted for age, sex, obesity, hypertension, diabetes, chronic kidney disease, and coronary heart disease to assess the relationship between assigned trajectory and incident HF. Results In the discovery set (n=747), we identified six trajectories of cardiac function based jointly on longitudinal changes in LVEF and E/A ratio (Figure 1). The pink (prevalence 50%) and light green (17%) trajectories showed increasing LVEF and decreasing E/A ratio with increasing age, while the red trajectory (22%) demonstrated a lack of increase in LVEF. The dark green trajectory (4%) demonstrated progressive LVEF decline, the orange trajectory (2%) steep LVEF decline and rise in E/A ratio, and the blue trajectory (4%) rising E/A ratio despite increasing in LVEF. Analysis of the ARIC-only participants (n=4,419) showed that trajectory membership was differentially associated with risk of incident HFpEF and HFrEF (Figure 2). Compared to the pink trajectory, membership in the orange trajectory was associated with incident HFpEF and HFrEF, the red and the dark green trajectory associated with HFrEF alone, and the blue trajectory with HFpEF alone. Conclusion(s) These results demonstrate the feasibility of identifying trajectories of cardiac function with multidimensional longitudinal data and may have implications for HF risk prediction.