Supportive care for patient with respiratory diseases: an umbrella review

  1. on behalf of COVID-19 Evidence and Recommendations Working Group
  2. Xufei Luo
  3. Meng Lv
  4. Xiaoqing Wang
  5. Xin Long
  6. Mengjuan Ren
  7. Xianzhuo Zhang
  8. Yunlan Liu
  9. Weiguo Li
  10. Qi Zhou
  11. Yanfang Ma
  12. Toshio Fukuoka
  13. Hyeong Sik Ahn
  14. Myeong Soo Lee
  15. Zhengxiu Luo
  16. Enmei Liu
  17. Xiaohui Wang
  18. Yaolong Chen

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.13.20064360: (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

    Software and Algorithms
    SentencesResources
    Search strategy: We performed a systematic search of Medline via PubMed, EMBASE, Web of Science, CNKI (China National Knowledge Infrastructure), Wanfang Data and CBM (China Biology Medicine disc) from their inception to 31 March 2020 with the terms (“COVID-19” OR “SARS-CoV-2” OR “2019 novel coronavirus” OR “2019-nCoV” OR “Wuhan coronavirus” OR “novel coronavirus” OR “Wuhan seafood market pneumonia virus” OR “MERS” OR “SARS” OR “Severe Acute Respiratory Syndrome” OR “Middle East Respiratory Syndrome Coronavirus” OR “Influenza”) AND (“Meta-analysis” OR “Systematic Review” OR “rapid review”) (The details of the search strategy can be found in the Supplementary Material 1).
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    In addition, we searched Google Scholar as well as reference lists of the identified articles, to find additional studies.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Three preprint services, including medRxiv (https://www.medrxiv.org/), bioRxiv (https://www.biorxiv.org/) and SSRN (https://www.ssrn.com/index.cfm/en/) were also searched to find relevant studies.
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    All statistical analyses were conducted in STATA 14.0.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    Nevertheless, our work has several limitations. First, we conducted a rapid literature searching and screening, and some relevant studies may have been missed. Second, none of the included systematic reviews focused on COVID-19, SARS or MERS, so they can be only used as indirect evidence. Finally, there was large heterogeneity between the included studies, and most primary studies included in these systematic reviews were observational studies, which may influence the reliability of the reviews. However, systematic reviews and meta-analyses of non-randomized studies can be meaningful and guide clinical research and practice, even if only by emphasizing the limitations of the available clinical evidence.

    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-20-3298
  3. Version published to 10.1101/2020.04.13.20064360v1 on medRxiv