Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort (MaastrICCht)

  1. Jeanette Tas
  2. Rob J J van Gassel
  3. Serge J H Heines
  4. Mark M G Mulder
  5. Nanon F L Heijnen
  6. Melanie J Acampo-de Jong
  7. Julia L M Bels
  8. Frank C Bennis
  9. Marcel Koelmann
  10. Rald V M Groven
  11. Moniek A Donkers
  12. Frank van Rosmalen
  13. Ben J M Hermans
  14. Steven JR Meex
  15. Alma Mingels
  16. Otto Bekers
  17. Paul Savelkoul
  18. Astrid M L Oude Lashof
  19. Joachim Wildberger
  20. Fabian H Tijssen
  21. Wolfgang Buhre
  22. Jan-Willem E M Sels
  23. Chahinda Ghossein-Doha
  24. Rob G H Driessen
  25. Pieter L Kubben
  26. Marcus L F Janssen
  27. Gerry A F Nicolaes
  28. Ulrich Strauch
  29. Zafer Geyik
  30. Thijs S R Delnoij
  31. Kim H M Walraven
  32. Coen DA Stehouwer
  33. Jeanine A M C F Verbunt
  34. Walther N.K.A Van Mook
  35. Susanne van Santen
  36. Ronny M Schnabel
  37. Marcel J H Aries
  38. Marcel C G van de Poll
  39. Dennis Bergmans
  40. Iwan C C van der Horst
  41. Sander van Kuijk
  42. Bas C T van Bussel

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Abstract

The course of the disease in SARS-CoV-2 infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational Maastricht Intensive Care COVID cohort (MaastrICCht). We incorporated serial measurements that harbour aetiological, diagnostic and predictive information. The study aims to investigate the heterogeneity of the natural course of critically ill patients with a SARS-CoV-2 infection.

Methods and analysis

Mechanically ventilated patients admitted to the intensive care with a SARS-CoV-2 infection will be included. We will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, ECGs, echocardiography as well as other imaging modalities to assess heterogeneity of the course of a SARS-CoV-2 infection in critically ill patients. The MaastrICCht is also designed to foster various other studies and registries and intends to create an open-source database for investigators. Therefore, a major part of the data collection is aligned with an existing national intensive care data registry and two international COVID-19 data collection initiatives. Additionally, we create a flexible design, so that additional measures can be added during the ongoing study based on new knowledge obtained from the rapidly growing body of evidence. The spread of the COVID-19 pandemic requires the swift implementation of observational research to unravel heterogeneity of the natural course of the disease of SARS-CoV-2 infection in mechanically ventilated patients. Our study design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht.

Ethics and dissemination

Ethical approval has been obtained from the medical ethics committee (Medisch Ethische Toetsingscommissie 2020-1565/3 00 523) of the Maastricht University Medical Centre+ (Maastricht UMC+), which will be performed based on the Declaration of Helsinki. During the pandemic, the board of directors of Maastricht UMC+ adopted a policy to inform patients and ask their consent to use the collected data and to store serum samples for COVID-19 research purposes. All study documentation will be stored securely for fifteen years after recruitment of the last patient. The results will be published in peer-reviewed academic journals, with a preference for open access journals, while particularly considering deposition of the manuscripts on a preprint server early.

Trial registration number

The Netherlands Trial Register (NL8613).

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  1. ScreenIT

    SciScore for 10.1101/2020.04.27.20080309: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The local institutional review board
    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: 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: 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 10.1136/bmjopen-2020-040175
  3. Version published to 10.1101/2020.04.27.20080309v1 on medRxiv