Pre-implant echocardiography plus EHR for post-LVAD risk stratification for survival: Single-center exploratory study.

Abstract

Purpose: Durable LVAD therapy improves survival for advanced heart failure, yet adverse outcomes remain common. We evaluated whether combining pre-implant echocardiography with routinely available Electronic Health Record (EHR) data yields clinically useful post-LVAD risk predictions to improve patient selection and perioperative management.

Methods: In this retrospective study (2015-2022), pre-implant apical four-chamber echocardiograms were processed via raw loops and U-Net segmentation. CNN embeddings were integrated with PCA-reduced EHR variables including demographics, laboratories, and hemodynamics. Survival models, including Cox proportional hazards and random survival forests, were trained on multimodal inputs. Performance was validated using stratified 5-fold cross-validation, targeting a primary endpoint of time to death or missed follow-up. Saliency mapping was utilized to ensure clinical interpretability of the model's features.

Results: Multimodal models achieved higher discrimination than single-modality models, with segmented-echo inputs outperforming raw videos (mean C-index of 0.711). Saliency mapping identified clinically coherent predictors: right ventricular and septal geometry on imaging, alongside renal, hepatic, and nutritional status from the EHR.

Conclusions: Integrating pre-implant echocardiography with EHR data enhances risk stratification survival for LVAD candidates. This multimodal approach identifies high-risk phenotypes, specifically right-heart and systemic frailty, providing a framework for personalized clinical decision support and future multicenter validation.