开发和验证 COVID-19 住院患者 40 天死亡风险预测模型。
Development and validation of a prognostic 40-day mortality risk model among hospitalized patients with COVID-19.
机构信息
Berry Consultants LLC, Austin, Texas, United States of America.
M.D. Anderson Cancer Center of the University of Texas, Houston, Texas, United States of America.
出版信息
PLoS One. 2021 Jul 30;16(7):e0255228. doi: 10.1371/journal.pone.0255228. eCollection 2021.
OBJECTIVES
The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations.
METHODS
We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset.
RESULTS
The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had >3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation <94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual's 40-day risk of mortality was generated as -14.258 + 13.460RS + 1.585(RS-2.524)^2-0.403*(RS-2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS.
CONCLUSIONS
A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19.
TRIAL REGISTRATION
Clinicaltrials.gov Identifier: NCT04347993.
目的
开发一种针对住院 COVID-19 患者的预后死亡风险模型，可能有助于患者的治疗计划、治疗策略的比较和公共卫生准备。
方法
我们回顾性分析了 2020 年 3 月 1 日至 2020 年 4 月 22 日期间在新泽西州美国 13 家医院网络住院的、聚合酶链反应（PCR）检测结果为 SARS-CoV-2 阳性的患者的电子健康记录，并随访至 2020 年 5 月 29 日。以第 40 天的死亡或出院为主要终点，我们首先使用单变量，然后使用逐步多变量比例风险模型，在数据集的一半中开发风险评分，在另一半中验证，并根据综合数据集将风险评分转换为患者水平的 40 天死亡率预测概率。
结果
研究人群包括 3123 名住院 COVID-19 患者；中位年龄 63 岁；60%为男性；42%有>3 种并存疾病。713 例（23%）患者在 COVID-19 住院后 40 天内死亡。从 22 个潜在候选因素中，有 6 个被发现是死亡的独立预测因素，并被纳入风险评分模型：年龄、入院时呼吸频率≥25/分钟、入院时氧饱和度<94%以及高血压、冠状动脉疾病或慢性肾脏疾病等预存合并症。风险评分在训练集和验证集中对死亡率具有高度预测性，在综合数据集中，风险评分每增加 1 单位，风险比为 1.80（95%可信区间，1.72，1.87）。使用风险评分 20 个相等大小的分箱内观察到的死亡率，可以生成一个预测个体 40 天死亡率风险的模型，为-14.258+13.460RS+1.585（RS-2.524）^2-0.403*（RS-2.524）^3。一个在线计算器可用于计算 40 天 COVID-19 死亡率风险评分，网址为 www.HackensackMeridianHealth.org/CovidRS。
结论
使用 6 个变量的风险评分能够预测 COVID-19 住院 40 天内的死亡率。
试验注册
Clinicaltrials.gov 标识符：NCT04347993。
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