Objective To develop and validate a prediction model of mortality in patients with COVID-19 attending hospital emergency rooms. Design Multivariable prognostic prediction model. Setting 127 Spanish hospitals. Participants Derivation (DC) and external validation (VC) cohorts were obtained from multicentre and single-centre databases, including 4035 and 2126 patients with confirmed COVID-19, respectively. Interventions Prognostic variables were identified using multivariable logistic regression. Main outcome measures 30-day mortality. Results Patients’ characteristics in the DC and VC were median age 70 and 61 years, male sex 61.0% and 47.9%, median time from onset of symptoms to admission 5 and 8 days, and 30-day mortality 26.6% and 15.5%, respectively. Age, low age-adjusted saturation of oxygen, neutrophil-to-lymphocyte ratio, estimated glomerular filtration rate by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, dyspnoea and sex were the strongest predictors of mortality. Calibration and discrimination were satisfactory with an area under the receiver operating characteristic curve with a 95% CI for prediction of 30-day mortality of 0.822 (0.806–0.837) in the DC and 0.845 (0.819–0.870) in the VC. A simplified score system ranging from 0 to 30 to predict 30-day mortality was also developed. The risk was considered to be low with 0–2 points (0%–2.1%), moderate with 3–5 (4.7%–6.3%), high with 6–8 (10.6%–19.5%) and very high with 9–30 (27.7%–100%). Conclusions A simple prediction score, based on readily available clinical and laboratory data, provides a useful tool to predict 30-day mortality probability with a high degree of accuracy among hospitalised patients with COVID-19. All data relevant to the study are included in the article or uploaded as supplementary information.

中文翻译：

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COVID-19 住院患者 30 天死亡率预测模型的开发和验证：COVID-19 SEIMC 评分

目的 开发和验证 COVID-19 住院急诊室患者死亡率的预测模型。设计多变量预后预测模型。设置 127 家西班牙医院。参与者推导 (DC) 和外部验证 (VC) 队列来自多中心和单中心数据库，分别包括 4035 和 2126 名确诊的 COVID-19 患者。干预 使用多变量逻辑回归确定预后变量。主要结果衡量 30 天死亡率。结果 DC和VC患者的特征为中位年龄70岁和61岁，男性61.0%和47.9%，出现症状到入院的中位时间分别为5天和8天，30天死亡率分别为26.6%和15.5% . 年龄、低年龄调整氧饱和度、中性粒细胞与淋巴细胞的比率、根据慢性肾脏病流行病学合作 (CKD-EPI) 方程估计的肾小球滤过率、呼吸困难和性别是死亡率的最强预测因子。校准和区分令人满意，受试者操作特征曲线下面积的 95% CI 预测 30 天死亡率在 DC 中为 0.822 (0.806-0.837)，在 VC 中为 0.845 (0.819-0.870)。还开发了一个从 0 到 30 的简化评分系统来预测 30 天死亡率。风险被认为是低的 0-2 分 (0%-2.1%)，中等的 3-5 (4.7%-6.3%)，高的 6-8 (10.6%-19.5%) 和非常高的 9 –30（27.7%–100%）。结论 基于现成的临床和实验室数据的简单预测评分，提供了一种有用的工具，可以高度准确地预测 COVID-19 住院患者的 30 天死亡率。与研究相关的所有数据都包含在文章中或作为补充信息上传。