Predictive Accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting
Abstract
Objective No systematic methods exist for triaging outpatients with severe conditions. Our previous pilot study suggested that the National Early Warning Score (NEWS) predicts admission and unexpected intensive care unit (ICU) transfer in outpatients. The Visensia Score Index (VSI) is another artificial intelligence-based Early Warning Score System that automatically analyzes data from bedside monitors. This study aimed to compare the predictive accuracy of NEWS and VSI in identifying potentially critically ill patients in outpatient settings. Methods This single-center retrospective cohort study was conducted at a 344-bed tertiary-care hospital in Japan. The study population comprised first-visit patients at an internal medicine clinic from June to November 2018. Age, sex, physiological measurements, NEWS, VSI, disposition, and outcomes were collected. Results 3,301 patients were included. A total of 108 (3.3%), 16 (0.5%), and 5 (0.2%) patients were admitted to the general ward, high-dependency unit (HDU), and ICU, respectively. The area under the curve (AUC) of NEWS for hospital admission, HDU or ICU admission, and ICU admission were 0.71 [95% confidence interval (CI, 0.66-0.76)]; 0.88 (95% CI, 0.80-0.97); and 1.00 (95% CI, 0.996-1.0), respectively, while those of VSI were 0.66 (95% CI, 0.60-0.71), 0.82 (95% CI, 0.71-0.93), and 0.97 (95% CI, 0.96-0.98). The AUC of NEWS was significantly superior to that of VSI for both hospital (p=0.03) and ICU admissions (p<0.01). Conclusion NEWS demonstrated a better discriminative performance than the VSI in this single-center outpatient cohort.
Related
- Comments on "Predictive Accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting."
- A novel meropenem dosing strategy for Outpatient Parenteral Antimicrobial Therapy (OPAT): a pilot pharmacokinetic/pharmacodynamic study in non-critically ill patients
- A novel predictive tool for pulmonary aspergillosis in critically ill patients with viral pneumonia: a multi-center, ambispective cohort study
- Predictive value of glucose metabolism indices for short-term outcomes in critically ill patients with congestive heart failure
- Diagnostic Performance of Color Doppler Ultrasound for Detecting Nuchal Cord and Associated Immediate Neonatal Outcomes at Term in Uganda: A Prospective Diagnostic‐Accuracy Cohort Study
BibTeX
@article{ehara2026predictive,
title = {{Predictive Accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting}},
author = {Jun Ehara and Sachiko Ohde and Eiji Hiraoka and Yosuke Homma and Shigeki Fujitani},
journal = {Internal Medicine},
year = {2026},
month = oct,
doi = {10.2169/internalmedicine.5756-25},
url = {https://www.jstage.jst.go.jp/article/internalmedicine/65/19/65_5756-25/_article},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Predictive Accuracy of Early Warning Score Systems for Detecting Critically Ill Patients in an Outpatient Setting
AU - Jun Ehara
AU - Sachiko Ohde
AU - Eiji Hiraoka
AU - Yosuke Homma
AU - Shigeki Fujitani
PY - 2026
DA - 2026/10/01
JO - Internal Medicine
DO - 10.2169/internalmedicine.5756-25
UR - https://www.jstage.jst.go.jp/article/internalmedicine/65/19/65_5756-25/_article
AB - Objective No systematic methods exist for triaging outpatients with severe conditions. Our previous pilot study suggested that the National Early Warning Score (NEWS) predicts admission and unexpected intensive care unit (ICU) transfer in outpatients. The Visensia Score Index (VSI) is another artificial intelligence-based Early Warning Score System that automatically analyzes data from bedside monitors. This study aimed to compare the predictive accuracy of NEWS and VSI in identifying potentially critically ill patients in outpatient settings. Methods This single-center retrospective cohort study was conducted at a 344-bed tertiary-care hospital in Japan. The study population comprised first-visit patients at an internal medicine clinic from June to November 2018. Age, sex, physiological measurements, NEWS, VSI, disposition, and outcomes were collected. Results 3,301 patients were included. A total of 108 (3.3%), 16 (0.5%), and 5 (0.2%) patients were admitted to the general ward, high-dependency unit (HDU), and ICU, respectively. The area under the curve (AUC) of NEWS for hospital admission, HDU or ICU admission, and ICU admission were 0.71 [95% confidence interval (CI, 0.66-0.76)]; 0.88 (95% CI, 0.80-0.97); and 1.00 (95% CI, 0.996-1.0), respectively, while those of VSI were 0.66 (95% CI, 0.60-0.71), 0.82 (95% CI, 0.71-0.93), and 0.97 (95% CI, 0.96-0.98). The AUC of NEWS was significantly superior to that of VSI for both hospital (p=0.03) and ICU admissions (p<0.01). Conclusion NEWS demonstrated a better discriminative performance than the VSI in this single-center outpatient cohort.
SN - 1349-7235
SN - 0918-2918
ER -