Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: an observational cohort study

Rishi K. Gupta, M. Marks, Thomas H A Samuels, Akish Luintel, T. Rampling, Humayra Chowdhury, Matteo Quartagno, A. Nair, M. Lipman, I. Abubakar, M. van Smeden, W. K. Wong, B. Williams, M. Noursadeghi
{"title":"Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: an observational cohort study","authors":"Rishi K. Gupta, M. Marks, Thomas H A Samuels, Akish Luintel, T. Rampling, Humayra Chowdhury, Matteo Quartagno, A. Nair, M. Lipman, I. Abubakar, M. van Smeden, W. K. Wong, B. Williams, M. Noursadeghi","doi":"10.1101/2020.07.24.20149815","DOIUrl":null,"url":null,"abstract":"The number of proposed prognostic models for coronavirus disease 2019 (COVID-19) is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation. We independently externally validated the performance of candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at the time of admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictors in univariable analyses. We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78, 95% CI 0.73–0.83), and a novel model for prediction of deterioration <14 days from admission (0.78, 95% CI 0.74–0.82). The most discriminating univariable predictors were admission oxygen saturation on room air for in-hospital deterioration (AUROC 0.76, 95% CI 0.71–0.81), and age for in-hospital mortality (AUROC 0.76, 95% CI 0.71–0.81). No prognostic model demonstrated consistently higher net benefit than these univariable predictors, across a range of threshold probabilities. Admission oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated here offered incremental value for patient stratification to these univariable predictors. Oxygen saturation on room air and patient age are strong predictors of deterioration and mortality, respectively, among hospitalised adults with COVID-19. None of the 22 prognostic models evaluated in this study adds incremental value to these univariable predictors. https://bit.ly/2Hg24TO","PeriodicalId":77419,"journal":{"name":"The European respiratory journal. Supplement","volume":"45 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"156","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The European respiratory journal. Supplement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2020.07.24.20149815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 156

Abstract

The number of proposed prognostic models for coronavirus disease 2019 (COVID-19) is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation. We independently externally validated the performance of candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at the time of admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictors in univariable analyses. We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78, 95% CI 0.73–0.83), and a novel model for prediction of deterioration <14 days from admission (0.78, 95% CI 0.74–0.82). The most discriminating univariable predictors were admission oxygen saturation on room air for in-hospital deterioration (AUROC 0.76, 95% CI 0.71–0.81), and age for in-hospital mortality (AUROC 0.76, 95% CI 0.71–0.81). No prognostic model demonstrated consistently higher net benefit than these univariable predictors, across a range of threshold probabilities. Admission oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated here offered incremental value for patient stratification to these univariable predictors. Oxygen saturation on room air and patient age are strong predictors of deterioration and mortality, respectively, among hospitalised adults with COVID-19. None of the 22 prognostic models evaluated in this study adds incremental value to these univariable predictors. https://bit.ly/2Hg24TO
住院成人COVID-19患者22种预后模型的系统评估和外部验证:一项观察性队列研究
提出的2019冠状病毒病(COVID-19)预后模型的数量正在迅速增长,但尚不清楚是否有适合广泛临床实施的模型。我们独立地从外部验证了候选预后模型的性能,这些模型是通过实时系统评价在最终诊断为COVID-19的连续住院成人中确定的。我们根据原始描述重建候选模型,并使用入院时测量的预测因子评估其原始预期结果的表现。我们评估了鉴别、校准和净效益,比较了治疗所有患者和不治疗患者的默认策略,以及单变量分析中最具鉴别性的预测因子。我们在411名COVID-19参与者中测试了22种候选预后模型,其中180例(43.8%)和115例(28.0%)分别达到临床恶化和死亡率的终点。受试者工作特征(AUROC)曲线下面积最大的是预测24小时恶化的NEWS2评分(0.78,95% CI 0.73-0.83)和预测入院后<14天恶化的新模型(0.78,95% CI 0.74-0.82)。最具鉴别性的单变量预测因子是入院时室内空气氧饱和度(AUROC为0.76,95% CI为0.71-0.81)和年龄(AUROC为0.76,95% CI为0.71-0.81)。在阈值概率范围内,没有预测模型显示出始终高于这些单变量预测因子的净效益。入院时室内空气氧饱和度和患者年龄分别是COVID-19住院成人病情恶化和死亡率的有力预测指标。在此评估的预后模型中,没有一个为这些单变量预测因子提供患者分层的增量价值。在COVID-19住院的成年人中,室内空气氧饱和度和患者年龄分别是病情恶化和死亡率的有力预测指标。在本研究中评估的22个预后模型中,没有一个为这些单变量预测因子增加了增量值。https://bit.ly/2Hg24TO
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信