Why the C-statistic is not informative to evaluate early warning scores and what metrics to use.
Why the C-statistic is not informative to evaluate early warning scores and what metrics to use.
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DOI：
10.1186/s13054-015-0999-1
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发表时间：
2015-08-13
期刊：
影响因子：
--
通讯作者：
Liebow M
中科院分区：
文献类型：
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作者：
Romero-Brufau S;Huddleston JM;Escobar GJ;Liebow M
通常用于报告预警分数(EWS)表现的指标，如接收器操作员特征曲线或C统计量下的面积，对于实施前分析没有用处。由于生理恶化的发生率极低，每个病例日为0.02，这些指标可能具有误导性。我们讨论了这一说法背后的统计推理，并提出了一种新的替代度量，更适合于EWS的操作。我们建议EWSS的实施前评估至少应包括两个指标：灵敏度；以及积极预测值、评估所需的数量或估计的警报率。我们还讨论了报告每个分界值的重要性。
Metrics typically used to report the performance of an early warning score (EWS), such as the area under the receiver operator characteristic curve or C-statistic, are not useful for pre-implementation analyses. Because physiological deterioration has an extremely low prevalence of 0.02 per patient-day, these metrics can be misleading. We discuss the statistical reasoning behind this statement and present a novel alternative metric more adequate to operationalize an EWS. We suggest that pre-implementation evaluation of EWSs should include at least two metrics: sensitivity; and either the positive predictive value, number needed to evaluate, or estimated rate of alerts. We also argue the importance of reporting each individual cutoff value.