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Infectious diseases
Protocol
Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis
  1. Xinxing Lai1,2,3,
  2. Jian Liu4,
  3. Tianyi Zhang1,5,
  4. Luda Feng1,5,
  5. Ping Jiang1,5,
  6. Ligaoge Kang6,
  7. Qiang Liu7,
  8. Ying Gao1,3
  1. 1Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
  2. 2Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University, Beijing, China
  3. 3Institute for Brain Disorders, Beijing University of Chinese Medicine, Beijing, China
  4. 4Department of TCM Pulmonary Diseases, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
  5. 5Beijing University of Chinese Medicine, Beijing, China
  6. 6Department of Emergency, Fangshan Hospital, Beijing University of Chinese Medicine, Beijing, China
  7. 7Center for Evidence-based Medicine, World Federation of Chinese Medicine Societies, Beijing, China
  1. Correspondence to Professor Ying Gao; gaoying973{at}163.com

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.

  • infectious diseases
  • public health
  • COVID-19
  • adult intensive & critical care
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2020-039813

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    Footnotes

    • Contributors XL and YG conceived the research question. TZ, LF, PJ and LK developed the search strategy and performed the preliminary search, screening and data extraction. QL and YG contributed to the methodological development of the protocol. XL and JL drafted the manuscript. QL and YG revised the manuscript and all authors developed and approved the final manuscript before submission.

    • Funding The study was funded by the Chinese Medicine Inheritance and Innovation Talent Project-National Leading Talent Support Program for Traditional Chinese Medicine (Grant [2018] No.12)

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.