ArticleRisk management and healthcare policy2022
Development and Validation of a Nomogram for Predicting Risk of Emergency Department Revisits in Chinese Older Patients.
Article in Risk management and healthcare policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine Learning-Based Prediction Model for 30-Day Emergency Department Revisits in a Medically Underserved Tertiary Hospital: Formative Retrospective Cohort Study.JMIR formative research · 2026Article
- The prevalence and factors of adverse health outcomes in Chinese older emergency patients: a cohort study.BMC geriatrics · 2025Article
- In-Hospital Mortality Prediction Model for Critically Ill Older Adult Patients Transferred from the Emergency Department to the Intensive Care Unit.Risk management and healthcare policy · 2023Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: The identification of older patients at risk of repeated emergency department (ED) visits is crucial for managing preventable adverse outcomes. This study aims to identify risk factors associated with ED revisits and to develop and validate a nomogram for predicting risk of geriatric ED revisits. Methods: This was a cohort study comprising 553 older patients, who attended the two tertiary hospitals EDs in China from August 2018 to February 2019 and were prospectively followed for any unplanned revisit within 1 year after discharge. Patients were randomly assigned to a training or validation set at a ratio of 2:1. Stepwise selection procedure was applied to select factors associated with ED revisits for inclusion in a multivariable logistic model from which a nomogram was elaborated. Discrimination, calibration and clinical utility of the nomogram were assessed using C-statistic, calibration plot, Hosmer-Lemeshow test, and decision curve analysis (DCA). Results: The final nomogram included four predictors for ED revisits: age, BMI, frailty and polypharmacy. Older patients having revisits were more likely to be frail (OR = 1.17, Conclusion: A nomogram incorporating four obtainable variables was constructed to individualize ED readmission risk in older patients. These patients may benefit from early triage and better-targeted care if considering the nomogram as a clinical decision aid.
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