ArticlePloS one2026
Development and internal validation of prediction models for ICU-level intervention and 14-day mortality at Medical Emergency Team activation: A retrospective cohort study.
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
backgroundMedical Emergency Team (MET) activation represents acute clinical deterioration requiring rapid decisions regarding escalation of care. Previous post-MET prediction studies have evaluated outcomes including unplanned intensive care unit (ICU) admission and mortality; however, ICU admission is a location-based outcome that may be influenced by institutional factors. Prediction based on treatment intensity rather than location of care has received less attention.
methodsWe conducted a retrospective single-center cohort study of adult patients undergoing MET activation on general wards at a tertiary-care hospital in Japan between May 2021 and December 2025. Two outcomes were evaluated: initiation of ICU-level interventions within 24 hours and all-cause 14-day mortality. ICU-level interventions were defined as the initiation of mechanical ventilation, vasopressor or inotropic infusion, renal replacement therapy, or polymyxin B hemoperfusion (PMX). Multivariable logistic regression and Cox proportional hazards models were developed using variables available at the time of MET activation. Model performance was evaluated using discrimination (C-index), calibration, decision curve analysis, and bootstrap-based internal validation.
resultsAmong 533 patients, 303 (56.8%) required ICU-level interventions and 147 (27.6%) died within 14 days. Lower albumin levels and higher blood urea nitrogen, potassium, and white blood cell count were associated with both outcomes, whereas higher heart rate was associated with 14-day mortality. The model demonstrated moderate discrimination for ICU-level intervention (C-index 0.721, 95% CI 0.660-0.745) and good discrimination for 14-day mortality (C-index 0.784, 95% CI 0.720-0.814). Calibration analyses indicated modest overfitting but generally good agreement between predicted and observed risks. Decision curve analysis demonstrated clinical net benefit across a range of threshold probabilities.
conclusionsIn this single-center cohort, treatment escalation and short-term mortality represented related but distinct dimensions of clinical risk. Defining intensive care need based on treatment intensity rather than ICU admission may provide an operational framework for risk stratification at MET activation. External validation is required before clinical implementation.
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