ArticleFrontiers in public health2026
A multidomain early warning model for 12-month adverse outcomes in older adults with multimorbidity: a risk-stratified public health approach.
Article in Frontiers in public health, 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
Objective: To develop and internally validate a multidomain early warning model for 12-month adverse outcomes in older adults with multimorbidity, and to explore its potential for risk-stratified follow-up. Methods: This retrospective study included 690 older adults (≥60 years) with multimorbidity from a Chinese tertiary hospital, split into derivation ( Results: The composite outcome occurred in 146 patients (21.2%). Seven predictors were retained: age ≥75 years, ≥4 chronic diseases, prior hospitalization, ADL impairment, malnutrition, depression, and chronic pain. The model showed good discrimination in the derivation set (AUC 0.847), random split validation set (AUC 0.826), and temporal validation set (AUC 0.819). Bootstrap internal validation yielded an optimism-corrected AUC of 0.831. Calibration was acceptable across all validation methods (calibration slopes: 0.94-1.02; Brier scores: 0.152-0.171). Using pragmatic thresholds, 41.2, 42.0, and 16.8% of patients were classified as low, intermediate, and high risk, respectively. The high-risk group accounted for 41.1% of all events. Network analysis revealed a prominent cardio-metabolic disease cluster. In a retrospective scenario analysis, a model-driven stratified intervention was projected to reduce composite adverse outcomes by 25.3%. Conclusion: This internally validated model identifies a small high-risk subgroup that carries a large share of adverse events. External validation in community health centers, secondary hospitals, and other regions is required before implementation. The model provides a preliminary framework for targeted follow-up and risk-informed planning, but its generalizability remains unproven.
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