Nosocomial infections among patients with COVID-19, SARS and MERS: a rapid review and meta-analysis

  1. on behalf of COVID-19 Evidence and Recommendations Working Group
  2. Qi Zhou
  3. Yelei Gao
  4. Xingmei Wang
  5. Rui Liu
  6. Peipei Du
  7. Xiaoqing Wang
  8. Xianzhuo Zhang
  9. Shuya Lu
  10. Zijun Wang
  11. Qianling Shi
  12. Weiguo Li
  13. Yanfang Ma
  14. Xufei Luo
  15. Toshio Fukuoka
  16. Hyeong Sik Ahn
  17. Myeong Soo Lee
  18. Enmei Liu
  19. Yaolong Chen
  20. Zhengxiu Luo
  21. Kehu Yang

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.14.20065730: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and Limitations: Our study included studies related to nosocomial infections among COVID-19, SARS and MERS patients. Our results can help the decision-making related to prevention, control and clinical management in hospitals. Some studies had missing data, and we used methods of meta-analyses of proportions to analyse those studies with available data, so the proportions estimated may not be accurate and similar to the actual data. Most of the results are based on low-quality research, so that the credibility of the results is low.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.21037/atm-20-3324
  3. Version published to 10.1101/2020.04.14.20065730v1 on medRxiv