Optimize speckle-tracking echocardiography screening in CKD patients: a TyG index-based nomogram model

Chronic kidney disease (CKD) patients with worsening left ventricular (LV) systolic function face significantly poorer clinical outcomes. While speckle-tracking echocardiography (STE)-derived global longitudinal strain (GLS) can sensitively detect early LV systolic dysfunction, indiscriminate routine STE screening in CKD populations may lead to unnecessary healthcare resource utilization. Therefore, identifying CKD patients at high risk of concurrent abnormal GLS in clinical practice may help optimize the selective use of STE. Notably, the triglyceride-glucose (TyG) index, as a reliable and readily accessible indicator for assessing insulin resistance, has demonstrated a close association with GLS in multiple studies. Therefore, this study aimed to develop a TyG index-based model to predict the risk of abnormal GLS in CKD patients, thereby providing a basis for optimizing screening strategies using STE.

This prospective cross-sectional study enrolled CKD patients from the Fifth Affiliated Hospital of Sun Yat-sen University between July 2023 to July 2024. All CKD patients underwent clinical examination, biochemistry measurement and transthoracic echocardiography.

Among 260 initially screened CKD patients, 212 were included after exclusions (median age: 47 years, male: 58%). Multivariable analysis identified male sex (OR = 2.77), diastolic blood pressure (OR = 1.07), high-density lipoprotein (OR = 0.36) and TyG index (OR = 4.55) as independent predictors of reduced GLS (< 20%). The developed nomogram model demonstrated robust predictive performance (AUC 0.838-0.842) and clinical utility across multiple risk thresholds in both training and validation cohorts.

The developed nomogram model could serve as an effective screening tool to optimize STE utilization in CKD patients, thereby conserving medical resources.