COVIDTrach: a prospective cohort study of mechanically ventilated patients with COVID-19 undergoing tracheostomy in the UK

  1. COVIDTrach collaborative

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Abstract

COVIDTrach is a UK multicentre prospective cohort study project that aims to evaluate the outcomes of tracheostomy in patients with COVID-19 receiving mechanical ventilation and record the incidence of SARS-CoV-2 infection among healthcare workers involved in the procedure.

Design

Data on patient demographic, clinical history and outcomes were entered prospectively and updated over time via an online database (REDCap). Clinical variables were compared with outcomes, with logistic regression used to develop a model for mortality. Participants recorded whether any operators tested positive for SARS-CoV-2 within 2 weeks of the procedure.

Setting

UK National Health Service departments involved in treating patients with COVID-19 receiving mechanical ventilation.

Participants

The cohort comprised 1605 tracheostomy cases from 126 UK hospitals collected between 6 April and 26 August 2020.

Main outcome measures

Mortality following tracheostomy, successful wean from mechanical ventilation and length of time from tracheostomy to wean, discharge from hospital, complications from tracheostomy, reported SARS-CoV-2 infection among operators.

Results

The median time from intubation to tracheostomy was 15 days (IQR 11, 21). 285 (18%) patients died following the procedure. 1229 (93%) of the survivors had been successfully weaned from mechanical ventilation at censoring and 1049 (81%) had been discharged from hospital. Age, inspired oxygen concentration, positive end-expiratory pressure setting, fever, number of days of ventilation before tracheostomy, C reactive protein and the use of anticoagulation and inotropic support independently predicted mortality. Six reports were received of operators testing positive for SARS-CoV-2 within 2 weeks of the procedure.

Conclusions

Tracheostomy appears to be safe in mechanically ventilated patients with COVID-19 and to operators performing the procedure and we identified clinical parameters that are predictive of mortality.

Trial registration number

The study is registered with ClinicalTrials.Gov ( NCT04572438 ).

Article activity feed

  1. Version published to 10.1136/bmjsit-2020-000077
  2. ScreenIT

    SciScore for 10.1101/2020.10.20.20216085: (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
    Procedures: Data was collected using an online survey tool (REDCap) with return codes issued to allow participants to update clinical outcomes prospectively.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    The study is registered with ClinicalTrials.
    ClinicalTrials
    suggested: (ClinicalTrials.gov, RRID:SCR_002309)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04572438RecruitingA Cohort Study of Mechanically Ventilated COVID-19 Patients …

    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.

  3. Version published to 10.1101/2020.10.20.20216085v2 on medRxiv
  4. Version published to 10.1101/2020.10.20.20216085v1 on medRxiv