ArticleBMC health services research2026
Evaluating the real-world utility of four physiological scores for prehospital interventions in resource-limited EMS systems: a population-based study of 15,720 cases.
Article in BMC health services research, 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
objectiveTo systematically evaluate the risk stratification performance of four physiological scoring systems-National Early Warning Score (NEWS), Rapid Acute Physiology Score (RAPS), Glasgow Coma Scale (GCS), and Shock Index (SI)-in prehospital emergency care within resource-limited settings, and to inform evidence-based triage strategies and intervention allocation.
methodsThis retrospective population-based cohort study analyzed 15,720 prehospital emergency cases from Shaodong Emergency Medical Center (2023-2024), a county-level EMS system operating under resource-constrained conditions in southern China. A novel analytical framework, integrating "score stratification × intervention behavior," was designed to assess the predictive consistency and clinical utility of the four scoring systems across four essential prehospital interventions: oxygen therapy, ECG monitoring, intravenous (IV) access, and fluid administration. Statistical methods included trend analysis, nonparametric effect size estimation, generalized linear mixed models (GLMMs), and an XGBoost machine learning algorithm.
resultsNEWS and RAPS demonstrated the strongest dose-response consistency in guiding intervention decisions. Although all effect sizes remained in the weak range (η² < 0.06), NEWS showed the highest trend strength for ECG monitoring (Z = 23.58, P < 0.001) and the largest effect size (η² = 0.0415), with RAPS showing a comparable value (η² = 0.0412). High-risk patients were significantly more likely to receive ECG monitoring than low-risk patients (OR = 2.691, 95% CI: 2.301-3.142). GCS was predictive primarily in patients with severe consciousness impairment (OR = 4.32, P < 0.001), while SI demonstrated minimal discriminatory value (η² < 0.01). In the XGBoost model, disease category (importance = 0.161) and NEWS (0.108) emerged as the most influential predictors of intervention intensity.
conclusionIn this real-world, resource-constrained EMS cohort, physiological scores exhibited limited discriminatory capacity. Nevertheless, NEWS and RAPS showed more consistent associations with intervention allocation than GCS or SI. Even modest stratification reduced decision variability, supporting an adjunctive role. Multicenter prospective studies are needed to establish actionable thresholds and validate their impact on intervention timeliness and patient outcomes.
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