Factors Associated with 28-day Critical Illness Development During the First Wave of COVID-19

  1. Uluhan Sili
  2. Pinar Ay
  3. Ahmet Topuzoglu
  4. Huseyin Bilgin
  5. Elif Tukenmez-Tigen
  6. Buket Ertürk-Sengel
  7. Dilek Yagcı-Çaglayik
  8. Baran Balcan
  9. Derya Kocakaya
  10. Sehnaz Olgun-Yildizeli
  11. Fethi Gul
  12. Beliz Bilgili
  13. Rabia Can-Sarinoglu
  14. Aysegul Karahasan-Yagci
  15. Lutfiye Mulazimoglu-Durmusoglu
  16. Emel Eryuksel
  17. Zekaver Odabasi
  18. Haner Direskeneli
  19. Sait Karakurt
  20. Ismail Cinel
  21. Volkan Korten

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Abstract

Objective: This study aimed to define the predictors of critical illness development within 28 days postadmission during the first wave of the COVID-19 pandemic. Materials and Methods: We conducted a prospective cohort study including 477 PCR-positive COVID-19 patients admitted to a tertiary care hospital in Istanbul from March 12 to May 12, 2020. Results: The most common presenting symptoms were cough, dyspnea, and fatigue. Critical illness developed in 45 (9.4%; 95% CI=7.0%-12.4%) patients. In the multivariable analysis, age (hazard ratio (HR)=1.05, p<0.001), number of comorbidities (HR=1.33, p=0.02), procalcitonin ≥0.25 µg/L (HR=2.12, p=0.03) and lactate dehydrogenase (LDH) ≥350 U/L (HR=2.04, p=0.03) were independently associated with critical illness development. The World Health Organization (WHO) ordinal scale for clinical improvement on admission was the strongest predictor of critical illness (HR=4.15, p<0.001). The patients hospitalized at the end of the study period had a much better prognosis compared to the patients hospitalized at the beginning (HR=0.14; p=0.02). The C-index of the model was 0.92. Conclusion: Age, comorbidity number, the WHO scale, LDH, and procalcitonin were independently associated with critical illness development. Mortality from COVID-19 seemed to be decreasing as the first wave of the pandemic advanced. Keywords: COVID-19, prospective cohort, critical illness, prognosis

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  1. Version published to 10.36519/idcm.2023.206
  2. ScreenIT

    SciScore for 10.1101/2020.10.09.20209775: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Approval: The study was approved by the ethics board of Marmara University, School of Medicine (09.2020.572).
    Consent: The requirement for written informed consent was waived by the 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: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. Although our hospital is one of the main pandemic hospitals within the region, this study is based on a single center’s experience. BMI information was lacking in 14.0% of the participants. We did not quantify the extent of pulmonary involvement on thoracic CT, which might predict the development of critical illness.

    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.

  3. Version published to 10.1101/2020.10.09.20209775v1 on medRxiv