ArticlePloS one2026
Vital signs and common blood tests improve the predictive power of the Hospital Frailty Risk Score to predict poor outcomes across all adult ages.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundFrailty is associated with poor health outcomes and is a public health challenge worldwide. The Hospital Frailty Risk Score (HFRS) has been widely used to identify patients at risk of frailty and predict poor outcomes including long length of stay (LOS) and in-hospital mortality for older patients. This study aimed to explore and determine variables that might influence the ability of the Hospital Frailty Risk Score to predict LOS and in-hospital mortality across all adult ages.
methodsThis is a retrospective cohort study using data from Queen Alexandra Hospital in Portsmouth, UK of consecutive patient admissions over 10 years between 01/01/2010 to 31/12/2019. The study included patients aged 16 years and older. The HFRS was calculated for each patient based on ICD-10 diagnostic codes with a 2-year look-back. The National Early Warning Score (NEWS) and the Laboratory Decision Tree Early Warning Score (LDT-EWS) were calculated for each patient. Vital signs and blood tests were the first available routine data from patients after admission. We developed logistic regression models (alone and adjusted) for 9 prediction periods of length of stay and 8 prediction periods of in-hospital mortality and assessed the model performance using AUROC.
resultsCombining HFRS with the LDT-EWS had the highest discrimination (AUROC ranging from 0.764 to 0.810) compared to adjusted models (AUROC ranging from 0.716 to 0.796) or HFRS alone (AUROC ranging from 0.723 to 0.798) for 9 periods of length of stay. For in-hospital mortality, combining HFRS with NEWS had the highest discrimination (AUROC ranging from 0.786 to 0.829) compared to HFRS alone or HFRS combined with other variables for 3, 7, 10 and 14-day mortality across all adult ages. And combining HFRS with LDT-EWS had the highest discrimination (AUROC ranging from 0.789 to 0.794) for mortality after more than 14 days across all adult ages.
conclusionsCombining HFRS with additional routinely available variables significantly improves the predictive power for length of stay and mortality. This is the first paper to show that LDT-EWS significantly improves the predictive power of Hospital Frailty Risk Scores to predict longer length of stay in hospital and later in-patient mortality across all adult ages. The predictive power of the HFRS was improved by NEWS for early in-patient mortality.
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