Acta Medica Nagasakiensia
Print ISSN : 0001-6055
ORIGINAL ARTICLES
The effectiveness of Modified Early Warning Score (MEWS) using individual-specific range in predicting pneumonia hospitalization among nursing home residents in Japan: Comparison with National Early Waring Score (NEWS)
Shunsuke MaetaSatoshi Mizukami PhDYoshihito Tomita PhDYutaka Date MD, PhDKazuhiko Arima MD, PhDKiyoshi Aoyagi MD, PhD
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2022 Volume 65 Issue 3 Pages 89-94

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Abstract

Aim: The purpose of this study was to compare the usefulness between the National Early Warning Score (NEWS), which uses the absolute value range, and the Modified Early Warning Score (MEWS), which considers individual-specific ranges (evaluated by mean and standard deviation [SD], relative measures), in predicting pneumonia hospitalization among nursing home residents. Methods: The current study was a retrospective, observational study. The subjects were 235 nursing home residents (75 men and 160 women; pneumonia group, n=62; non-pneumonia group, n=173). The mean and SD of each vital sign (systolic blood pressure, heart rate, body temperature, and oxygen saturation) of each subject recorded over 28 days was calculated. In the pneumonia group, the points at the date of hospitalization were aggregated to derive the NEWS and MEWS. In the non-pneumonia group, the point at the 35th day from the start of the nursing home stay was aggregated to derive the NEWS and MEWS. Results: The area under the curve (AUC) for predicting pneumonia hospitalization was 0.80 (95% confidence interval [CI], 0.72- 0.88) for NEWS and 0.92 (95%CI, 0.87-0.97) for MEWS using individual-specific ranges. The AUC of MEWS using individual-specific ranges was significantly greater than that of NEWS (p < 0.0001). When 3 was used as a cutoff value in MEWS, the Youden Index was the best value (0.75). Sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.97, 0.91, and 0.92, respectively. Conclusion: Our MEWS system using individual-specific ranges showed good performance in predicting hospitalization for pneumonia among nursing home residents.

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© 2022 by Nagasaki University School of Medicine
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