University of Wisconsin Madison, 5228, Medicine; Division of Pulmonary and Critical Care, Madison, Wisconsin, United States;
Brigham and Women's Hospital Department of Medicine, 370908, Division of Renal Medicine, Boston, Massachusetts, United States.
Am J Respir Crit Care Med. 2021 Aug 15;204(403-411):403-11. doi: 10.1164/rccm.202012-4547OC.
Variation in hospital mortality has been described for coronavirus disease 2019 (COVID-19), but the factors that explain these differences remain unclear.
Our objective was to utilize a large, nationally representative dataset of critically ill adults with COVID-19 to determine which factors explain mortality variability.
In this multicenter cohort study, we examined adults hospitalized in intensive care units with COVID-19 at 70 United States hospitals between March and June 2020. The primary outcome was 28-day mortality. We examined patient-level and hospital-level variables. Mixed-effects logistic regression was used to identify factors associated with interhospital variation. The median odds ratio (OR) was calculated to compare outcomes in higher- vs. lower-mortality hospitals. A gradient boosted machine algorithm was developed for individual-level mortality models.
A total of 4,019 patients were included, 1537 (38%) of whom died by 28 days. Mortality varied considerably across hospitals (0-82%). After adjustment for patient- and hospital-level domains, interhospital variation was attenuated (OR decline from 2.06 [95% CI, 1.73-2.37] to 1.22 [95% CI, 1.00-1.38]), with the greatest changes occurring with adjustment for acute physiology, socioeconomic status, and strain. For individual patients, the relative contribution of each domain to mortality risk was: acute physiology (49%), demographics and comorbidities (20%), socioeconomic status (12%), strain (9%), hospital quality (8%), and treatments (3%).
There is considerable interhospital variation in mortality for critically ill patients with COVID-19, which is mostly explained by hospital-level socioeconomic status, strain, and acute physiologic differences. Individual mortality is driven mostly by patient-level factors. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).
新冠肺炎（COVID-19）患者的医院死亡率存在差异，但尚不清楚导致这些差异的因素。
本研究旨在利用一项包含大量重症 COVID-19 成年患者的全国代表性数据集，确定哪些因素可以解释死亡率的差异。
本多中心队列研究纳入了 2020 年 3 月至 6 月期间美国 70 家医院的重症监护病房中 COVID-19 住院患者。主要结局为 28 天死亡率。我们评估了患者和医院层面的变量。采用混合效应逻辑回归模型确定与医院间差异相关的因素。计算中位数优势比（OR）来比较高死亡率和低死亡率医院的结局。开发了个体水平死亡率模型的梯度提升机算法。
共纳入 4019 例患者，其中 1537 例（38%）患者在 28 天内死亡。各医院的死亡率差异较大（0-82%）。在调整了患者和医院层面的各因素后，医院间的差异减弱（OR 从 2.06[95%置信区间：1.73-2.37]下降至 1.22[95%置信区间：1.00-1.38]），最大的变化发生在调整了急性生理学、社会经济地位和应变后。对于个体患者，各因素对死亡率风险的相对贡献为：急性生理学（49%）、人口统计学和合并症（20%）、社会经济地位（12%）、应变（9%）、医院质量（8%）和治疗（3%）。
COVID-19 重症患者的死亡率存在较大的医院间差异，主要由医院层面的社会经济地位、应变和急性生理差异解释。个体死亡率主要由患者层面的因素驱动。本文为开放获取，根据知识共享署名非商业性无衍生协议（CC BY-NC-ND 4.0）进行许可。
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