Suppr超能文献

COVID-19 患者不良结局的预后因素:一项全领域系统回顾和荟萃分析。

Prognostic factors for adverse outcomes in patients with COVID-19: a field-wide systematic review and meta-analysis.

机构信息

Dept of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.

Dept of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.

出版信息

Eur Respir J. 2022 Feb 3;59(2). doi: 10.1183/13993003.02964-2020. Print 2022 Feb.

Abstract

INTRODUCTION

The individual prognostic factors for coronavirus disease 2019 (COVID-19) are unclear. For this reason, we aimed to present a state-of-the-art systematic review and meta-analysis on the prognostic factors for adverse outcomes in COVID-19 patients.

METHODS

We systematically reviewed PubMed from 1 January 2020 to 26 July 2020 to identify non-overlapping studies examining the association of any prognostic factor with any adverse outcome in patients with COVID-19. Random-effects meta-analysis was performed, and between-study heterogeneity was quantified using I statistic. Presence of small-study effects was assessed by applying the Egger's regression test.

RESULTS

We identified 428 eligible articles, which were used in a total of 263 meta-analyses examining the association of 91 unique prognostic factors with 11 outcomes. Angiotensin-converting enzyme inhibitors, obstructive sleep apnoea, pharyngalgia, history of venous thromboembolism, sex, coronary heart disease, cancer, chronic liver disease, COPD, dementia, any immunosuppressive medication, peripheral arterial disease, rheumatological disease and smoking were associated with at least one outcome and had >1000 events, p<0.005, I<50%, 95% prediction interval excluding the null value, and absence of small-study effects in the respective meta-analysis. The risk of bias assessment using the Quality in Prognosis Studies tool indicated high risk of bias in 302 out of 428 articles for study participation, 389 articles for adjustment for other prognostic factors and 396 articles for statistical analysis and reporting.

CONCLUSIONS

Our findings could be used for prognostic model building and guide patient selection for randomised clinical trials.

摘要

简介

新型冠状病毒病 2019(COVID-19)的个体预后因素尚不清楚。因此,我们旨在对 COVID-19 患者不良结局的预后因素进行最先进的系统评价和荟萃分析。

方法

我们系统地检索了 2020 年 1 月 1 日至 2020 年 7 月 26 日的 PubMed 数据库,以确定非重叠研究,这些研究检查了任何预后因素与 COVID-19 患者任何不良结局的关联。采用随机效应荟萃分析,并使用 I 统计量量化研究间异质性。通过应用 Egger 回归检验评估小样本效应的存在。

结果

我们确定了 428 篇符合条件的文章,这些文章共用于 263 项荟萃分析,这些荟萃分析研究了 91 个独特的预后因素与 11 个结局的关联。血管紧张素转换酶抑制剂、阻塞性睡眠呼吸暂停、咽痛、静脉血栓栓塞史、性别、冠心病、癌症、慢性肝病、慢性阻塞性肺疾病、痴呆、任何免疫抑制药物、外周动脉疾病、风湿性疾病和吸烟与至少一种结局相关,且事件数>1000,p<0.005,I<50%,95%预测区间排除零值,且各自荟萃分析中无小样本效应。使用预后研究质量工具进行的偏倚风险评估表明,428 篇文章中有 302 篇在研究参与方面存在高偏倚风险,389 篇在调整其他预后因素方面存在高偏倚风险,396 篇在统计分析和报告方面存在高偏倚风险。

结论

我们的研究结果可用于预后模型的构建,并为随机临床试验的患者选择提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da31/8576809/59ce4df156ee/ERJ-02964-2020.01.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验