Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.
Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.
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DOI：
10.1016/s2213-2600(20)30559-2
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发表时间：
2021-04
期刊：
影响因子：
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通讯作者：
ISARIC4C Investigators
中科院分区：
文献类型：
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作者：
Gupta RK;Harrison EM;Ho A;Docherty AB;Knight SR;van Smeden M;Abubakar I;Lipman M;Quartagno M;Pius R;Buchan I;Carson G;Drake TM;Dunning J;Fairfield CJ;Gamble C;Green CA;Halpin S;Hardwick HE;Holden KA;Horby PW;Jackson C;Mclean KA;Merson L;Nguyen-Van-Tam JS;Norman L;Olliaro PL;Pritchard MG;Russell CD;Scott-Brown J;Shaw CA;Sheikh A;Solomon T;Sudlow C;Swann OV;Turtle L;Openshaw PJM;Baillie JK;Semple MG;Noursadeghi M;ISARIC4C Investigators
迫切需要预测急性COVID-19病例临床恶化风险的预后模型，为临床管理决策提供信息。我们开发并验证了一个多变量逻辑回归模型，用于医院内临床恶化（定义为任何急救支持或重症监护要求，国际严重急性呼吸道和新发感染联盟冠状病毒临床表征联盟前瞻性招募的高度疑似或确诊COVID-19的连续住院成人患者中，（ISARIC 4C）在英格兰，苏格兰和威尔士的260家医院进行的研究。根据先前的预后评分和描述与COVID-19预后相关的常规测量生物标志物的新文献，考虑将先验指定的候选预测因子纳入模型。我们使用内部-外部交叉验证来评估开发队列中八个国家卫生服务（NHS）地区的歧视，校准和临床效用。我们进一步验证了最终的模型，从一个额外的NHS地区（伦敦）的数据。 纳入了74944名参与者（在2020年2月6日至8月26日期间招募），其中73948名具有可用结局的参与者中有31924名（43.2%）符合复合临床恶化结局。 在66705名参与者的开发队列中进行的内部-外部交叉验证中，所选模型（包括在入院时常规测量的11个预测因子）在所有8个NHS地区显示出一致的区分，校准和临床实用性。 在来自伦敦（n=8239）的保留数据中，该模型显示出相似的一致性性能（C-统计量0·77 [95% CI 0·76至0·78];大样本校准0·00 [-0统计量05至0·05]）;校准斜率0·96 [0·91至1·01]），并且比任何其他可重复的预后模型都更大的净效益。4C恶化模型具有很强的临床实用性和普适性潜力，可用于预测临床恶化，并为因COVID-19住院的成年人提供决策信息。国家卫生研究所（NIHR）、英国医学研究理事会、威康信托基金会、国际发展部、比尔和梅林达·盖茨基金会、欧洲预防（再）新发流行病欧盟平台、利物浦大学新发和人畜共患感染NIHR健康保护研究单位（HPRU）、伦敦帝国理工学院呼吸道感染NIHR HPRU。
Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal–external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal–external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [–0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.