Refining risk prediction in geriatric heart failure: the emergency heart failure mortality risk grade‑BI model under scrutiny

Risk stratification is critical for managing acute heart failure in older adults, yet existing tools often underperform in geriatric populations. Özdemir recently introduced the EHMRG‑BI model, integrating brain natriuretic peptide and endotracheal intubation with the Emergency Heart Failure Mortality Risk Grade score to improve 30‑day mortality prediction. While the model demonstrates improved discrimination in a single‑center derivation cohort, several methodological considerations warrant attention. The inclusion of intubation, a treatment decision rather than a baseline characteristic, may introduce bias and limit its utility as an arrival‑time tool. The absence of key geriatric domains such as frailty, functional status, and cognitive impairment may result in residual confounding. Additionally, modelling BNP as a linear predictor disregards its well‑documented non‑linear association with mortality. This Matters Arising offers a perspective on these challenges and proposes refinements, including external validation, integration of geriatric assessments, and flexible BNP modelling, to strengthen the model's clinical applicability.