Improving predictive performance of Early Warning Scores by including trends in observations

The results of this study confirm that, not only can the performance of models predicting clinical deterioration be increased by including trends, but that a logistic regression-based model with very few predictors can predict the risk of deterioration better than current non-trend models. Thus, models incorporating trends have the potential to prevent deterioration in more patients than contemporary early warning scores, however further validation is necessary.

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Publication Details

Journal
Resuscitation
Published
2025-10-04
DOI
https://doi.org/10.1016/j.resuscitation.2025.110853
Citations
1
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35
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article

Improving predictive performance of Early Warning Scores by including trends in observations

David Prytherch, Jim Briggs, Ina Kostakis, Raphael A. Ehmann
1 citations
Resuscitation
Sepsis Diagnosis and Treatment
1.35
article

Improving predictive performance of Early Warning Scores by including trends in observations

David Prytherch, Jim Briggs, Ina Kostakis, Raphael A. Ehmann
article en
1 citations

Abstract

The results of this study confirm that, not only can the performance of models predicting clinical deterioration be increased by including trends, but that a logistic regression-based model with very few predictors can predict the risk of deterioration better than current non-trend models. Thus, models incorporating trends have the potential to prevent deterioration in more patients than contemporary early warning scores, however further validation is necessary.

ResuscitationVol. 217
Queen Alexandra Hospital (GB), University of Portsmouth (GB)
Openalex Percentile: Top 15%
Sepsis Diagnosis and Treatment
1.35
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