The COVID-19 Early Detection in Doctors and Healthcare Workers (CEDiD) Study: study protocol for a prospective observational trial

  1. Alexander Zargaran
  2. Dina Radenkovic
  3. Chelsea Trengrove
  4. Gill Arbane
  5. Kariem El-Boghdadly
  6. Rocio Martinez-Nunez
  7. Anne Greenough

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Abstract

Background

The global COVID-19 pandemic has caused worldwide disruption with its exponential spread mandating national and international lockdown measures. Hospital-associated transmission has been identified as a major factor in the perpetuation of COVID-19, with healthcare workers at high-risk of becoming infected with SARS-CoV-2 and representing important vectors for spread, but not routinely having their clinical observations monitored or being tested for COVID-19.

Methods

A single-center, prospective observational study of 60 healthcare workers will explore how many healthcare workers in high-risk areas develop COVID-19 infection over a thirty day period. High-risk areas are defined as COVID positive wards, the intensive care unit or the accident and emergency department. Healthcare workers (HCWs) will be recruited and have daily self-administered nasopharyngeal SARS-CoV-2 PCR tests. They will also be provided with a wearable medical device to measure their clinical observations during non-working hours, and be asked to complete a daily self-reported symptom questionnaire over the study period. Statistical analysis will assess the proportion of healthcare workers who develop COVID-19 infection as a primary objective, with secondary objectives exploring what symptoms are developed, time-to-event, and deviations in clinical observations.

Discussion

At present clinical observations, symptoms and COVID-19 PCR swabs are not routinely undertaken for healthcare workers. If the CEDiD (COVID-19 Early Detection in Doctors and Healthcare Workers) study is successful, it will provide useful information for workforce decisions in reducing hospital-associated transmission of COVID-19. The data will help in determining whether there are early warning signs for development of COVID-19 infections amongst healthcare workers and may contribute to the evidence base advocating for more regular testing of healthcare workers’ observations, symptoms and COVID-19 status.

Trial registration

ClinicalTrials.gov, NCT04363489 . Registered on 27 th July 2020

Article activity feed

  1. Version published to 10.1101/2020.08.11.20172502v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.08.11.20172502: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: They will be self-obtained by HCWs, who will have consented to do this every day for 30 days after reading the informed consent form when enrolling in the study.
    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:
    Trial Rationale: Strengths and Limitations: In this cohort study, participants will have swabs daily for the duration of the study, in which we will assess the presence of SARS-CoV-2 with the potential of measuring viral titres to provide an insight into the optimum testing strategy. Symptoms and severity can vary depending on factors; including comorbidities, ethnicity, age and sex. As such, the CEDiD Study will seek to include a representative sample. The limitations include timing as the fluctuations in rate of new infections of COVID-19 are variable on a daily basis. However, recruitment will be of HCWs who are in direct face-to-face contact with COVID positive patients. If successful, the CEDiD Study will provide important information for healthcare providers in advance of any possible future peaks of infection to prevent spread of disease and ensure minimal disruption to vital healthcare service provision. By leveraging advances in telehealth, medical devices and data analytics, it is hoped that this study will identify new strategies to facilitate the early identification of COVID-19. Trial Status: The CEDiD Study started recruitment of participants in August 2020.

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

    IdentifierStatusTitle
    NCT04363489Not yet recruitingThe CEDiD Study (COVID-19 Early Diagnosis in Doctors and Hea…

    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 10.1101/2020.08.11.20172502v1 on medRxiv