Dr Knight and colleagues report about a large-scale external validation of the 4C (ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) Coronavirus Clinical Characterisation Consortium) prediction models to predict in-hospital outcomes in patients admitted to a hospital because of COVID-19.1 The models use commonly available information to predict the probability of in-hospital deterioration and mortality (https://isaric4c.net/risk/). While the models require quite a few variables, they do allow for missingness of some predictors, which facilitates their use in practice. The ISARIC4C consortium was able to compile data from 76 588 patients from 306 hospitals and nine NHS regions of England, Scotland and Wales. The high frequency of outcome events (37.4% deteriorated and 25.1% died) allowed for very precise estimates of discrimination and calibration in the entire study population, but also in subgroups. Another strength is the temporal validation. The validation showed good performance of both models, similar to the predictive performance in the development cohort that consisted of patients hospitalised during …

中文翻译：

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验证 4C 预测模型以告知 COVID-19 患者的护理：临床应用的最后步骤

Knight 博士及其同事报告了对 4C（ISARIC（国际严重急性呼吸道和新兴感染联盟）冠状病毒临床特征联盟）预测模型的大规模外部验证，以预测因 COVID- 19.1 模型使用常用信息来预测院内恶化和死亡率的概率 (https://isaric4c.net/risk/)。虽然这些模型需要相当多的变量，但它们确实允许一些预测变量的缺失，这有助于它们在实践中的使用。ISARIC4C 联盟能够汇编来自英格兰、苏格兰和威尔士的 306 家医院和 9 个 NHS 地区的 76 588 名患者的数据。结果事件的高频率（37.4% 恶化和 25. 1% 死亡）允许对整个研究人群以及亚组的歧视和校准进行非常精确的估计。另一个优势是时间验证。验证显示两种模型的良好性能，类似于开发队列中的预测性能，该队列包括在……期间住院的患者。