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

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Abstract

Objectives

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).

Related collections

Most cited references 35

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Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Fei Zhou, Ting Yu, Ronghui Du … (2020)

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

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Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Paul A. Harris, Robert Taylor, Robert Thielke … (2009)

Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.

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Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

Zunyou Wu, Jennifer M. McGoogan (2020)

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Author and article information

Journal

Journal ID (nlm-ta): BMJ Surg Interv Health Technol

Journal ID (iso-abbrev): BMJ Surg Interv Health Technol

Journal ID (hwp): bmjsit

Journal ID (publisher-id): bmjsit

Title: BMJ Surgery, Interventions, & Health Technologies

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2631-4940

Publication date (Print): July 2021

Publication date (Electronic): 8 July 2021

Publication date PMC-release: 8 July 2021

Volume: 3

Issue: 1

Electronic Location Identifier: e000077

Affiliations

[1] departmentDivision of Surgery & Interventional Science , University College London , London, UK

Author notes

[Correspondence to ] Nick JI Hamilton; nick.hamilton@ 123456ucl.ac.uk

Article

Publisher ID: bmjsit-2020-000077

DOI: 10.1136/bmjsit-2020-000077

PMC ID: 8275367

SO-VID: 13e7be1b-b2c2-4892-9790-1b473ab40a3e

License:

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/.

History

Date received : 19 December 2020

Date accepted : 09 June 2021

Funding

Funded by: Wellcome Trust / UCL Therapeutic Acceleration Support (TAS) Fund - Covid-19 Rapid Response Funding call;

Award ID: BRC732/JK/101400

Custom metadata

special-feature unlocked

Keywords: covid-19,ear–nose–throat devices,anaesthesiology devices,cohort study

Data availability:

Keywords: covid-19, ear–nose–throat devices, anaesthesiology devices, cohort study