Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study.
Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study.
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DOI：
10.1136/bmjopen-2020-040729
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发表时间：
2020-09-25
期刊：
影响因子：
2.9
通讯作者：
Marchionni N
中科院分区：
文献类型：
--
作者：
Fumagalli C;Rozzini R;Vannini M;Coccia F;Cesaroni G;Mazzeo F;Cola M;Bartoloni A;Fontanari P;Lavorini F;Marcucci R;Morettini A;Nozzoli C;Peris A;Pieralli F;Pini R;Poggesi L;Ungar A;Fumagalli S;Marchionni N
COVID-19期间出现的几种生理异常与死亡率增加有关。在本研究中，我们的目标是根据住院分流后不久可用的一组变量，开发一种临床风险评分，以预测COVID-19患者的住院死亡率。回顾性队列研究收集了2020年2月22日（首次入院日期）至2020年4月10日期间在位于北方和意大利中部的两家意大利三级医院连续收治的516名COVID-19患者。因COVID-19入院的≥18岁的连续性患者。根据患者的生存状态（“死亡”vs“存活”），比较分诊后容易获得的简单临床和实验室结果，目的是确定与死亡率相关的基线变量。这些被用于建立COVID-19住院死亡风险评分（COVID-19 MRS）。平均年龄为67±13岁（平均值±SD），66.9%为男性。使用考克斯回归分析，年龄增加的三分位数（≥75岁，高年龄组vs <62岁，低年龄组：HR 7.92; p<0.001）和慢性疾病数量（≥4 vs 0-1：HR 2.09; p=0.007），呼吸频率（HR 1.04/单位增加; p=0.001），PaO 2/FiO 2（HR 0.995每单位增加; p<0.001），血清肌酐（HR 1.34/单位增加; p<0.001）和血小板计数（HR 0.995/单位增加; p=0.001）是死亡率的预测因子。所有六个预测因子都用于构建COVID-19 MRS（曲线下面积0.90，95%CI 0.87至0.93），这被证明在对低、中和高院内死亡风险患者进行分层时具有高度准确性（p<0.001）。COVID-19 MRS是一种快速、独立于操作员且廉价的临床工具，可客观预测COVID-19患者的死亡率。该评分可能有助于分流，以指导COVID-19患者早期分配到最适当的护理水平。
Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage. Retrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020. Consecutive patients≥18 years admitted for COVID-19. Simple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS). Mean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001). The COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.
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影响因子：
158.5
作者：
Li, Qun;Guan, Xuhua;Feng, Zijian
通讯作者：
Feng, Zijian
影响因子：
168.9
作者：
Huang, Chaolin;Wang, Yeming;Cao, Bin
通讯作者：
Cao, Bin
影响因子：
39
作者：
Wu, Chaomin;Chen, Xiaoyan;Song, Yuanlin
通讯作者：
Song, Yuanlin
影响因子：
5
作者：
Lippi, Giuseppe;Plebani, Mario;Henry, Brandon Michael
通讯作者：
Henry, Brandon Michael
DOI：
10.1001/jama.2020.6775
发表时间：
2020-01-01
期刊：
JAMA, Journal of the American Medical Association
影响因子：
--
作者：
Richardson, Safiya;Hirsch, Jamie S.;,
通讯作者：
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