我们确定与SARS-CoV-2感染有关的因素，与住院、重症监护室入院和死亡有关，并制定临床预测规则。回顾性队列研究，共380,081例SARS-CoV-2感染患者，时间为2020年3月1日至2022年1月9日，其中包括46,402例患者参加急诊科，有关生命体征的数据。为了推导和外部验证预测规则，考虑了不同的时期：新出现Omega变异毒株之前和之后。收集的数据包括社会人口学数据、COVID-19疫苗接种状况、基线共患症和治疗、其他背景数据和在急诊科的分诊时的生命体征。使用Lasso惩罚的多元Logistic回归模型开发了急诊科和整个样本的预测模型。在多变量模型中，急诊科患者死亡的普遍预测因素是年龄大、男性、未接种疫苗、痴呆症、心力衰竭、肝肾疾病、偏瘫或截瘫、凝血障碍、间质性肺疾病、恶性肿瘤、慢性全身性类固醇使用、体温升高、氧饱和度降低和血压心率改变。不良演变的预测因素相同，除了肝病外，并包括囊性纤维化。类似的预测因素与住院有关，包括肝病、动脉高血压和免疫抑制剂的基线处方。类似的模型也适用于没有生命体征的整个样本。我们提出了基于基本信息、易于计算、高预测性并适用于当前Omega变异毒株的风险量表，可以帮助管理基层、急 cares 急诊科和住院患者。版权所有©2023年作者。Elsevier B.V.保留所有权利。

We identify factors related to SARS-CoV-2 infection linked to hospitalization, ICU admission, and mortality and develop clinical prediction rules.Retrospective cohort study of 380,081 patients with SARS-CoV-2 infection from March 1, 2020 to January 9, 2022, including a subsample of 46,402 patients who attended Emergency Departments (EDs) having data on vital signs. For derivation and external validation of the prediction rule, two different periods were considered: before and after emergence of the Omicron variant, respectively. Data collected included sociodemographic data, COVID-19 vaccination status, baseline comorbidities and treatments, other background data and vital signs at triage at EDs. The predictive models for the EDs and the whole samples were developed using multivariate logistic regression models using Lasso penalization.In the multivariable models, common predictive factors of death among EDs patients were greater age; being male; having no vaccination, dementia; heart failure; liver and kidney disease; hemiplegia or paraplegia; coagulopathy; interstitial pulmonary disease; malignant tumors; use chronic systemic use of steroids, higher temperature, low O2 saturation and altered blood pressure-heart rate. The predictors of an adverse evolution were the same, with the exception of liver disease and the inclusion of cystic fibrosis. Similar predictors were found to be related to hospital admission, including liver disease, arterial hypertension, and basal prescription of immunosuppressants. Similarly, models for the whole sample, without vital signs, are presented.We propose risk scales, based on basic information, easily-calculable, high-predictive that also function with the current Omicron variant and may help manage such patients in primary, emergency, and hospital care.Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.