From the Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia (MB, CH, MHE).
J Am Board Fam Med. 2021 Feb;34(Suppl):S113-S126. doi: 10.3122/jabfm.2021.S1.200429.
The aim of this systematic review is to summarize the best available evidence regarding individual risk factors, simple risk scores, and multivariate models that use patient characteristics, vital signs, comorbidities, and laboratory tests relevant to outpatient and primary care settings.
Medline, WHO COVID-19, and MedRxIV databases were searched; studies meeting inclusion criteria were reviewed in parallel, and variables describing study characteristics, study quality, and risk factor data were abstracted. Study quality was assessed using the Quality in Prognostic Studies tool. Random effects meta-analysis of relative risks (categorical variables) and unstandardized mean differences (continuous variables) was performed; multivariate models and clinical prediction rules were summarized qualitatively.
A total of 551 studies were identified and 22 studies were included. The median or mean age ranged from 38 to 68 years. All studies included only inpatients, and mortality rates ranged from 3.2% to 50.5%. Individual risk factors most strongly associated with mortality included increased age, c-reactive protein (CRP), d-dimer, heart rate, respiratory rate, lactate dehydrogenase, and procalcitonin as well as decreased oxygen saturation, the presence of dyspnea, and comorbid coronary heart and chronic kidney disease. Independent predictors of adverse outcomes reported most frequently by multivariate models include increasing age, increased CRP, decreased lymphocyte count, increased lactate dehydrogenase, elevated temperature, and the presence of any comorbidity. Simple risk scores and multivariate models have been proposed but are often complex, and most have not been validated.
Our systematic review identifies several risk factors for adverse outcomes in COVID-19-infected inpatients that are often available in the outpatient and primary care settings: increasing age, increased CRP or procalcitonin, decreased lymphocyte count, decreased oxygen saturation, dyspnea on presentation, and the presence of comorbidities. Future research to develop clinical prediction models and rules should include these predictors as part of their core data set to develop and validate pragmatic outpatient risk scores.
本系统评价旨在总结有关门诊和初级保健环境中个体危险因素、简单风险评分以及使用患者特征、生命体征、合并症和实验室检查的多变量模型的最佳现有证据。
检索了 Medline、WHO COVID-19 和 MedRxIV 数据库；平行审查符合纳入标准的研究，并提取描述研究特征、研究质量和危险因素数据的变量。使用预后研究质量工具评估研究质量。对相对风险（分类变量）和未标准化均数差（连续变量）进行随机效应荟萃分析；定性总结多变量模型和临床预测规则。
共确定了 551 项研究，其中 22 项研究被纳入。中位数或平均年龄为 38 至 68 岁。所有研究均仅纳入住院患者，死亡率范围为 3.2%至 50.5%。与死亡率最密切相关的个体危险因素包括年龄增加、C 反应蛋白（CRP）、D-二聚体、心率、呼吸频率、乳酸脱氢酶和降钙素原以及氧饱和度降低、呼吸困难和合并冠心病和慢性肾脏病。多变量模型报告的不良结局的独立预测因素包括年龄增加、CRP 增加、淋巴细胞计数减少、乳酸脱氢酶升高、体温升高和任何合并症。已经提出了简单的风险评分和多变量模型，但它们通常很复杂，并且大多数尚未经过验证。
本系统评价确定了 COVID-19 感染住院患者不良结局的几个危险因素，这些危险因素在门诊和初级保健环境中经常存在：年龄增加、CRP 或降钙素原增加、淋巴细胞计数减少、氧饱和度降低、出现呼吸困难以及合并症。未来开发临床预测模型和规则的研究应将这些预测因素纳入其核心数据集，以开发和验证实用的门诊风险评分。
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