Features of creatine-kinase in COVID-19 patients within various specific periods: A cohort study

  1. Shanshan Wan
  2. Gaojing Qu
  3. Hui Yu
  4. Haoming Zhu
  5. Guoxin Huang
  6. Lei Chen
  7. Meiling Zhang
  8. Jiangtao Liu
  9. Bin Pei

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Abstract

Background

Coronavirus disease 2019 (COVID-19) has been declared as a threat to the global. Due to the lack of efficient treatments, indicators were urgently needed during the evolvement of disease to analyze the illness and prognosis, and prevent the aggravation of COVID-19.

Methods

Patients’ general information, clinical type, all CK values and outcome were collected. CK value of all cases during disease course started from different initial time were analyzed.

Results

All cases underwent 504 tests of CK since symptom onset and the median value was 51.7 (35.0-91.5) U/L. The first median value on the day 8 from exposure onset was 78.1 (69.1-85.8) U/L then showed an upward trend from the day 8 to the day 12 (reaching a peak of 279.3 U/L), finally showed a fluctuation decline after the day 12. The CK median value in critical cases reached the peak (625.5 U/L) on the transforming date, and then decreased rapidly to the normal range. Before death, the CK median value in dead cases firstly increased until the day −14 with a peak as 470.0 U/L, then decreased with fluctuation until day −2, and finally increased again on the day 0.

Conclusions

CK reached its peak on the day when it became critical type, dynamic detection of CK can guide clinical judgment of prognosis. The increase of CK is a high risk factor of death. Severe cell damage 2 weeks before death might determines the outcome of the disease even if CK drops to the normal range afterward.

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    SciScore for 10.1101/2020.10.28.20221119: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the ethics review board of Xiangyang No.1 People’s Hospital (No. 2020GCP012) and registered at the Chinese Clinical Trial Registry as ChiCTR2000031088.
    Consent: Informed consent from patients has been exempted since this study does not involve patients’ personal privacy neither incur greater than the minimal risk.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    2.5 Statistical analysis: All statistical analyses were performed through SPSS 20.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    All graphs were processed through GraphPad Prism 8.0 and Photoshop CC 14.2 software.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Photoshop
    suggested: (Adobe Photoshop, RRID:SCR_014199)

    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 10.1101/2020.10.28.20221119v1 on medRxiv