• Pediatr Crit Care Me · Sep 2020

    Observational Study

    A Vital Sign-Based Model to Predict Clinical Deterioration in Hospitalized Children.

    • Anoop Mayampurath, Priti Jani, Yangyang Dai, Robert Gibbons, Dana Edelson, and Matthew M Churpek.
    • Department of Pediatrics, University of Chicago, Chicago, IL.
    • Pediatr Crit Care Me. 2020 Sep 1; 21 (9): 820-826.

    ObjectivesClinical deterioration in hospitalized children is associated with increased risk of mortality and morbidity. A prediction model capable of accurate and early identification of pediatric patients at risk of deterioration can facilitate timely assessment and intervention, potentially improving survival and long-term outcomes. The objective of this study was to develop a model utilizing vital signs from electronic health record data for predicting clinical deterioration in pediatric ward patients.DesignObservational cohort study.SettingAn urban, tertiary-care medical center.PatientsPatients less than 18 years admitted to the general ward during years 2009-2018.InterventionsNone.Measurements And Main ResultsThe primary outcome of clinical deterioration was defined as a direct ward-to-ICU transfer. A discrete-time logistic regression model utilizing six vital signs along with patient characteristics was developed to predict ICU transfers several hours in advance. Among 31,899 pediatric admissions, 1,375 (3.7%) experienced the outcome. Data were split into independent derivation (yr 2009-2014) and prospective validation (yr 2015-2018) cohorts. In the prospective validation cohort, the vital sign model significantly outperformed a modified version of the Bedside Pediatric Early Warning System score in predicting ICU transfers 12 hours prior to the event (C-statistic 0.78 vs 0.72; p < 0.01).ConclusionsWe developed a model utilizing six commonly used vital signs to predict risk of deterioration in hospitalized children. Our model demonstrated greater accuracy in predicting ICU transfers than the modified Bedside Pediatric Early Warning System. Our model may promote opportunities for timelier intervention and risk mitigation, thereby decreasing preventable death and improving long-term health.

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