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Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis.
BMJ Open. 2020 12 24; 10(12):e039813.BO

Abstract

INTRODUCTION

With the threat of a worldwide pandemic of COVID-19, it is important to identify the prognostic factors for critical conditions among patients with non-critical COVID-19. Prognostic factors and models may assist front-line clinicians in rapid identification of high-risk patients, early management of modifiable factors, appropriate triaging and optimising the use of limited healthcare resources. We aim to systematically assess the clinical, laboratory and imaging predictors as well as prediction models for severe or critical illness and mortality in patients with COVID-19.

METHODS AND ANALYSIS

All peer-reviewed and preprint primary articles with a longitudinal design that focused on prognostic factors or models for critical illness and mortality related to COVID-19 will be eligible for inclusion. A systematic search of 11 databases including PubMed, EMBASE, Web of Science, Cochrane Library, CNKI, VIP, Wanfang Data, SinoMed, bioRxiv, Arxiv and MedRxiv will be conducted. Study selection will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data extraction will be performed using the modified version of the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and quality will be evaluated using the Newcastle-Ottawa Scale and the Quality In Prognosis Studies tool. The association between prognostic factors and outcomes of interest will be synthesised and a meta-analysis will be conducted with three or more studies reporting a particular factor in a consistent manner.

ETHICS AND DISSEMINATION

Ethical approval was not required for this systematic review. We will disseminate our findings through publication in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD 42020178798.

Authors+Show Affiliations

Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, China. Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China.Department of TCM Pulmonary Diseases, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Beijing University of Chinese Medicine, Beijing, China.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Beijing University of Chinese Medicine, Beijing, China.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Beijing University of Chinese Medicine, Beijing, China.Department of Emergency, Fangshan Hospital, Beijing University of Chinese Medicine, Beijing, China.Center for Evidence-based Medicine, World Federation of Chinese Medicine Societies, Beijing, China.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China gaoying973@163.com. Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China.

Pub Type(s)

Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Systematic Review

Language

eng

PubMed ID

33361074

Citation

Lai, Xinxing, et al. "Clinical, Laboratory and Imaging Predictors for Critical Illness and Mortality in Patients With COVID-19: Protocol for a Systematic Review and Meta-analysis." BMJ Open, vol. 10, no. 12, 2020, pp. e039813.
Lai X, Liu J, Zhang T, et al. Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis. BMJ Open. 2020;10(12):e039813.
Lai, X., Liu, J., Zhang, T., Feng, L., Jiang, P., Kang, L., Liu, Q., & Gao, Y. (2020). Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis. BMJ Open, 10(12), e039813. https://doi.org/10.1136/bmjopen-2020-039813
Lai X, et al. Clinical, Laboratory and Imaging Predictors for Critical Illness and Mortality in Patients With COVID-19: Protocol for a Systematic Review and Meta-analysis. BMJ Open. 2020 12 24;10(12):e039813. PubMed PMID: 33361074.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis. AU - Lai,Xinxing, AU - Liu,Jian, AU - Zhang,Tianyi, AU - Feng,Luda, AU - Jiang,Ping, AU - Kang,Ligaoge, AU - Liu,Qiang, AU - Gao,Ying, Y1 - 2020/12/24/ PY - 2020/12/28/entrez PY - 2020/12/29/pubmed PY - 2021/1/7/medline KW - COVID-19 KW - adult intensive & critical care KW - infectious diseases KW - public health SP - e039813 EP - e039813 JF - BMJ open JO - BMJ Open VL - 10 IS - 12 N2 - INTRODUCTION: With the threat of a worldwide pandemic of COVID-19, it is important to identify the prognostic factors for critical conditions among patients with non-critical COVID-19. Prognostic factors and models may assist front-line clinicians in rapid identification of high-risk patients, early management of modifiable factors, appropriate triaging and optimising the use of limited healthcare resources. We aim to systematically assess the clinical, laboratory and imaging predictors as well as prediction models for severe or critical illness and mortality in patients with COVID-19. METHODS AND ANALYSIS: All peer-reviewed and preprint primary articles with a longitudinal design that focused on prognostic factors or models for critical illness and mortality related to COVID-19 will be eligible for inclusion. A systematic search of 11 databases including PubMed, EMBASE, Web of Science, Cochrane Library, CNKI, VIP, Wanfang Data, SinoMed, bioRxiv, Arxiv and MedRxiv will be conducted. Study selection will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data extraction will be performed using the modified version of the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and quality will be evaluated using the Newcastle-Ottawa Scale and the Quality In Prognosis Studies tool. The association between prognostic factors and outcomes of interest will be synthesised and a meta-analysis will be conducted with three or more studies reporting a particular factor in a consistent manner. ETHICS AND DISSEMINATION: Ethical approval was not required for this systematic review. We will disseminate our findings through publication in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD 42020178798. SN - 2044-6055 UR - https://www.unboundmedicine.com/medline/citation/33361074/Clinical_laboratory_and_imaging_predictors_for_critical_illness_and_mortality_in_patients_with_COVID_19:_protocol_for_a_systematic_review_and_meta_analysis_ DB - PRIME DP - Unbound Medicine ER -