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Predictive accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting
Jun Ehara1,2,3, Sachiko Ohde2, Eiji Hiraoka1
1Department of Internal Medicine, Tokyo Bay Urayasu Ichikawa Medical Center, Japan.
The National Early Warning Score (NEWS) is more effective than the Visensia Score Index (VSI) for identifying critically ill outpatients. This study found NEWS superior in predicting hospital and intensive care unit admissions.
Area of Science:
- Critical Care Medicine
- Health Services Research
- Clinical Decision Support
Background:
- Systematic methods for triaging severe outpatients are lacking.
- Previous research indicated the National Early Warning Score (NEWS) predicts outpatient admission and ICU transfer.
- The Visensia Score Index (VSI) is an AI-based system analyzing bedside monitor data.
Purpose of the Study:
- To compare the predictive accuracy of NEWS and VSI in identifying potentially critically ill patients in outpatient settings.
- To evaluate the performance of two early warning scores in a real-world clinical environment.
Main Methods:
- A single-center retrospective cohort study in Japan.
- Included 3,301 first-visit internal medicine outpatients.
- Collected data on demographics, physiological measurements, NEWS, VSI, disposition, and outcomes.
Main Results:
- NEWS showed a significantly superior area under the curve (AUC) compared to VSI for hospital admission (0.71 vs. 0.66, p=0.03) and ICU admission (1.00 vs. 0.97, p<0.01).
- NEWS demonstrated better discriminative performance in predicting general ward, high-dependency unit (HDU), and ICU admissions.
Conclusions:
- The National Early Warning Score (NEWS) outperformed the Visensia Score Index (VSI) in predicting critical illness in this outpatient cohort.
- NEWS is a more effective tool for early detection and triage of high-risk outpatients.
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