To evaluate the prognostic value of three-dimensional echocardiography-derived left atrioventricular coupling index (LACI) in patients with chronic kidney disease (CKD) and concomitant heart failure with preserved ejection fraction (HFpEF). An analysis of 108 patients with CKD combined with HFpEF was conducted. Participants were categorized into three groups based on LACI, and differences in clinical and echocardiographic characteristics between groups were assessed. Independent associations between LACI and clinical outcomes were assessed using Cox proportional hazards regression modeling. In addition, an analysis was performed to determine the predictive performance of LACI for adverse cardiovascular events by calculating the area under the curve (AUC) and the optimal threshold. The median LACI in this study was 0.25. When stratified by tertiles, patients in the high LACI group (> 0.33) were significantly older, had more advanced CKD stages, and had more severe left ventricular diastolic dysfunction (LVDD) (all P < 0.05). With increasing LACI levels, the proportion of grade 1 LVDD progressively decreased while grade 3 LVDD increased (7%, 21%, 58%; P < 0.001). An LACI ≥ 0.235 demonstrated discriminative capability for moderate-to-severe LVDD (AUC = 0.739, P < 0.001). Multivariable Cox proportional hazards regression confirmed LACI as an independent predictor of major clinical outcomes (HR = 1.32, 95% CI: 0.792-0.894, P < 0.001). The optimal cutoff value of 0.26 (AUC = 0.843, P < 0.001) effectively stratified high-risk patients (log-rank P < 0.001). Net reclassification improvement (NRI) analysis demonstrated that incorporating LACI significantly enhanced the incremental predictive value of traditional clinical models. LACI, quantified by three-dimensional echocardiography (3DE), correlates with the severity of LVDD. LACI is an independent predictor of adverse clinical outcomes in patients with CKD combined with HFpEF, providing an objective quantitative metric that can guide therapeutic decision-making in this high-risk population.
Zhang et al. (Thu,) studied this question.