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BMJ Publishing Group, BMJ Open, 4(11), p. e045849, 2021

DOI: 10.1136/bmjopen-2020-045849

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Performance of universal early warning scores in different patient subgroups and clinical settings: a systematic review

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

ObjectiveTo assess predictive performance of universal early warning scores (EWS) in disease subgroups and clinical settings.DesignSystematic review.Data sourcesMedline, CINAHL, Embase and Cochrane database of systematic reviews from 1997 to 2019.Inclusion criteriaRandomised trials and observational studies of internal or external validation of EWS to predict deterioration (mortality, intensive care unit (ICU) transfer and cardiac arrest) in disease subgroups or clinical settings.ResultsWe identified 770 studies, of which 103 were included. Study designs and methods were inconsistent, with significant risk of bias (high: n=16 and unclear: n=64 and low risk: n=28). There were only two randomised trials. There was a high degree of heterogeneity in all subgroups and in national early warning score (I2=72%–99%). Predictive accuracy (mean area under the curve; 95% CI) was highest in medical (0.74; 0.74 to 0.75) and surgical (0.77; 0.75 to 0.80) settings and respiratory diseases (0.77; 0.75 to 0.80). Few studies evaluated EWS in specific diseases, for example, cardiology (n=1) and respiratory (n=7). Mortality and ICU transfer were most frequently studied outcomes, and cardiac arrest was least examined (n=8). Integration with electronic health records was uncommon (n=9).ConclusionMethodology and quality of validation studies of EWS are insufficient to recommend their use in all diseases and all clinical settings despite good performance of EWS in some subgroups. There is urgent need for consistency in methods and study design, following consensus guidelines for predictive risk scores. Further research should consider specific diseases and settings, using electronic health record data, prior to large-scale implementation.PROSPERO registration numberPROSPERO CRD42019143141.