Disease Control and Prevention Center, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
Disease Control and Prevention Center, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan; AMR Clinical Reference Center, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
J Infect Chemother. 2021 Jul;27(7):1043-1050. doi: 10.1016/j.jiac.2021.04.008. Epub 2021 Apr 12.
Most of the currently used prognostic models for COVID-19 are based on Western cohorts, but it is unknown whether any are applicable to patients with COVID-19 in Japan.
This retrospective cohort study included 160 patients with COVID-19 who were admitted to the National Center for Global Health and Medicine between January 26, 2020 and July 25, 2020. We searched PubMed for prognostic models for COVID-19. The predicted outcome was initiation of respiratory support or death. Performance of the candidate models was evaluated according to discrimination and calibration. We recalibrated the intercept of each model with our data. We also updated each model by adding β2-microglobulin (β2MG) to the model and recalculating the intercept and the coefficient of β2MG.
Mean patient age was 49.8 years, 68% were male, 88.7% were Japanese. The study outcomes occurred in 15 patients, including two deaths. Two-hundred sixty-nine papers were screened, and four candidate prognostic models were assessed. The model of Bartoletti et al. had the highest area under receiver operating characteristic curve (AUC) (0.88; 95% confidence interval 0.81-0.96). All four models overestimated the probability of occurrence of the outcome. None of the four models showed statistically significant improvement in AUCs by adding β2MG.
Our results suggest that the existing prediction models for COVID-19 overestimate the probability of occurrence of unfavorable outcomes in a Japanese cohort. When applying a prediction model to a different cohort, it is desirable to evaluate its performance according to the prevalent health situation in that region.
目前用于 COVID-19 的大多数预后模型都是基于西方队列的，但尚不清楚这些模型中是否有任何一个适用于日本的 COVID-19 患者。
本回顾性队列研究纳入了 2020 年 1 月 26 日至 2020 年 7 月 25 日期间入住国立全球卫生与医学研究中心的 160 例 COVID-19 患者。我们在 PubMed 上检索 COVID-19 的预后模型。预测结果为开始呼吸支持或死亡。根据判别和校准评估候选模型的性能。我们用我们的数据重新校准每个模型的截距。我们还通过向模型中添加β2-微球蛋白（β2MG）并重新计算截距和β2MG 的系数来更新每个模型。
患者平均年龄为 49.8 岁，68%为男性，88.7%为日本人。研究结果发生在 15 例患者中，包括 2 例死亡。筛选出 269 篇论文，并评估了四个候选预后模型。Bartoletti 等人的模型具有最高的接受者操作特征曲线（AUC）（0.88；95%置信区间 0.81-0.96）。所有四个模型都高估了不良结局发生的概率。在添加β2MG 后，四个模型的 AUC 均无统计学显著改善。
我们的结果表明，现有的 COVID-19 预测模型高估了日本队列中不良结局发生的概率。当将预测模型应用于不同的队列时，根据该地区的流行健康状况评估其性能是可取的。
