@article{discovery10126121,
            note = {This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.},
       publisher = {BMJ},
           month = {May},
         journal = {BMJ Open},
            year = {2021},
          volume = {11},
          number = {4},
           title = {Performance of universal early warning scores in different patient subgroups and clinical settings: a systematic review},
        abstract = {OBJECTIVE: To assess predictive performance of universal early warning scores (EWS) in disease subgroups and clinical settings.

DESIGN: Systematic review.


DATA SOURCES: Medline, CINAHL, Embase and Cochrane database of systematic reviews from 1997 to 2019.

INCLUSION CRITERIA: Randomised 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.

RESULTS: We 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).

CONCLUSION: Methodology 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 NUMBER: PROSPERO CRD42019143141.},
             url = {http://dx.doi.org/10.1136/bmjopen-2020-045849},
          author = {Alhmoud, B and Bonnici, T and Patel, R and Melley, D and Williams, B and Banerjee, A}
}