Sep 2026· Perfusion· pp.
2676591261485086
· 0 citations· 29 references
Medicine
TL;DR
HFRS is independently associated with 90-day mortality in patients undergoing VA ECMO, and incorporating frailty into pre-ECMO evaluation may enhance prognostication and inform patient selection and clinical decision-making.
Abstract
BackgroundFrailty is increasingly recognized as a key determinant of outcomes in critically ill patients, yet its utility among patients receiving venoarterial extracorporeal membrane oxygenation (VA ECMO) remains unclear. We evaluated the hospital frailty risk score (HFRS) as a risk factor of 90-day mortality in VA ECMO patients.MethodsWe conducted a retrospective analysis of VA ECMO patients at Johns Hopkins Hospital from 2016 to 2024. HFRS was derived from ICD-10 codes. An optimal frailty cut point was determined using maximally selected rank statistics, and patients were subsequently stratified into high (>10) and low (<=10) frailty groups. Cox proportional hazards models evaluated the association between frailty and mortality, adjusting for demographics, comorbidities, and clinical variables.Results180 patients receiving VA ECMO were included (median age:53 years, 46.2% female). Overall, 25 patients (13.9%) were classified as high frailty (HFRS >10) and 155 (86.1%) as low frailty (HFRS≤10). Of the 180 patients, 80 patients survived 90-days following initial ECMO cannulation. Median HFRS was higher among non-survivors (4.9 vs 3.4), with a greater proportion classified as high frailty (18.0% vs 8.8%). In multivariable Cox regression adjusting for demographics, comorbidities, and clinical covariates, low HFRS remained independently associated with reduced 90-day mortality (HR=0.47, 95% CI 0.26-0.87, p=0.017), while obesity (HR=10.44) and older age (HR 1.02) were independently associated with increased mortality.ConclusionHFRS is independently associated with 90-day mortality in patients undergoing VA ECMO. Incorporating frailty into pre-ECMO evaluation may enhance prognostication and inform patient selection and clinical decision-making.
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