Institute of Health Informatics, University College London, London, UK.
University College London Hospitals NHS Trust, London, UK.
BMJ Open. 2021 Apr 8;11(4):e045849. doi: 10.1136/bmjopen-2020-045849.
To assess predictive performance of universal early warning scores (EWS) in disease subgroups and clinical settings.
Systematic review.
Medline, CINAHL, Embase and Cochrane database of systematic reviews from 1997 to 2019.
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.
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 (I=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).
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 CRD42019143141.
评估通用早期预警评分（EWS）在疾病亚组和临床环境中的预测性能。
系统评价。
1997 年至 2019 年间，Medline、CINAHL、Embase 和 Cochrane 系统评价数据库。
对 EWS 进行内部或外部验证，以预测疾病亚组或临床环境中恶化（死亡率、转入重症监护病房（ICU）和心脏骤停）的随机试验和观察性研究。
我们确定了 770 项研究，其中 103 项被纳入。研究设计和方法不一致，存在较高的偏倚风险（高：n=16 和不确定：n=64 和低风险：n=28）。仅有两项随机试验。所有亚组和国家早期预警评分（I=72%-99%）中均存在高度异质性。在医学（0.74；0.74 至 0.75）和外科（0.77；0.75 至 0.80）以及呼吸疾病（0.77；0.75 至 0.80）环境中，预测准确性（平均曲线下面积；95%CI）最高。很少有研究评估 EWS 在特定疾病中的应用，例如心脏病学（n=1）和呼吸科（n=7）。死亡率和 ICU 转移是最常研究的结果，而心脏骤停研究最少（n=8）。与电子健康记录的整合很少见（n=9）。
尽管 EWS 在某些亚组中表现良好，但 EWS 的验证研究方法和质量不足以推荐其在所有疾病和所有临床环境中使用。迫切需要按照预测风险评分的共识指南，在方法和研究设计方面保持一致。在大规模实施之前，应使用电子健康记录数据进一步研究特定疾病和环境。
PROSPERO 注册号：PROSPERO CRD42019143141。
