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Nandini Nair

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Review Open access Aug 2026

Recalibrating Risk: A Call for South Asian-Focused Heart Failure Prediction Models

Background: Heart failure (HF) represents the final common pathway of diverse cardiovascular disorders, including coronary artery disease, primary myocardial pathology, and abnormalities of cardiac conduction. These conditions arise from an interplay of genetic, environmental, and psychosocial influences, making it essential to understand these determinants to improve risk prediction and prevention. Multiple biological pathways of inflammation, fibrosis, coagulation, oxidative stress, lipid dysregulation, endothelial dysfunction, and metabolic disturbances are shaped by inherited susceptibility and modifiable exposures. Together, these mechanisms drive HF development and progression, though their relative contributions vary across populations. Methods: PubMed and Google Scholar were searched for clinical, biomedical, and interdisciplinary studies published between 1 January 2000, and 31 December 2025. Keywords included “Asian,” “adult,” “India,” “heart failure,” “risk assessment,” “prognosis,” and “predictive value.” Studies were included if they focused on South Asian Indian adults, with priority given to original research, systematic reviews, and meta-analyses. Pediatric studies and those centered on other ethnic groups were excluded. Results: Among South Asian Indians, cardiovascular disease burden remains disproportionately high compared with Western populations. Unique genetic architecture, environmental exposures, and sociocultural factors appear to contribute to earlier onset and more aggressive disease. Identifying population-specific genetic variants, clarifying psychosocial influences, and addressing environmental risks may help reduce these disparities. Conclusions: This qualitative review highlights key gaps in current knowledge. A deeper understanding of these determinants could refine HF risk stratification, guide targeted prevention strategies, and reduce the growing cardiovascular burden in South Asian Indians. There is an urgent need for South Asian specific HF risk prediction models.

Nandini Nair, Dongping Du, Aiswarya J. Pillai et al. · 0 citations
Jul 2026

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

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.

Gabriel Farias Cacao, Dongping Du, Nandini Nair · 0 citations