Biomarkers in predicting mortality in hemodialysis patients: recent advances

: Patients undergoing maintenance hemodialysis face annual mortality rates of 15-27%, with cardiovascular causes accounting for more than half of all deaths. Despite advances in dialytic technology, conventional prognostic models derived from the general population systematically underestimate risk in end-stage renal disease, failing to capture the complexity of uremic pathophysiology that drives this excess mortality: immune dysregulation, chronic inflammation, oxidative stress, vascular calcification, uremic cardiomyopathy, protein-energy wasting, and accelerated vascular aging. This narrative review synthesizes current evidence on biomarkers predicting all-cause and cardiovascular mortality in haemodialysis patients, spanning established markers (albumin, CRP, ferritin, hemoglobin, high-sensitivity troponins, and NT-proBNP) to an emerging frontier encompassing IL-6, PTX3, sST2, galectin-3, FGF-23, Klotho, and multi-omics signatures. We further examine composite neutrophil-derived indices, adipokines, and mineral metabolism markers as tools for pathway-specific risk interrogation. The evidence converges on a clear practical message: combination and dynamics outperform single, static measurements. Multi-biomarker models consistently outperform individual markers, and longitudinal trajectories carry prognostic information, with divergence between survivors and non-survivors detectable many months before death, that a single time-point value cannot replicate. Advances in artificial intelligence and multi-omics further support this shift toward dynamic, personalized risk stratification, though these approaches remain at an early, largely exploratory stage. Critically, clinical translation remains limited by the lack of dialysis-specific thresholds, poor standardization, and the absence of randomized evidence demonstrating that biomarker-guided strategies improve outcomes. Bridging this gap between prognostic insight and clinical application remains the central challenge of precision nephrology.