Myocardial characteristics as the prognosis for COVID-19 patients

  1. Jianguo Zhang
  2. Daoyin Ding
  3. Can Cao
  4. Jinhui Zhang
  5. Xing Huang
  6. Peiwen Fu
  7. Guoxin Liang
  8. Wenrong Xu
  9. Zhimin Tao

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Abstract

Background

Amid the crisis of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), front-line clinicians in collaboration with backstage medical researchers analyzed clinical characteristics of COVID-19 patients and reported the prognosis using myocardial data records upon hospitalization.

Methods

We reported 135 cases of laboratory-confirmed COVID-19 patients admitted in The First People’s Hospital of Jiangxia District in Wuhan, China. Demographic data, medical history, and laboratory parameters were taken from inpatient records and compared between patients at the Intensive Care Unit (ICU) and non-ICU isolation wards for prognosis on disease severity. In particular, survivors and non-survivors upon ICU admission were compared for prognosis on disease mortality.

Results

For COVID-19 patients, blood test results showed more significantly deranged values in the ICU group than those in non-ICU. Among those parameters for ICU patients, myocardial variables including troponin T, creatine kinase isoenzymes, myoglobin, were found significantly higher in non-survivors than in survivors.

Conclusions

Upon hospitalization abnormal myocardial metabolism in COVID-19 patients could be prognostic indicators of a worsened outcome for disease severity and mortality.

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    SciScore for 10.1101/2020.05.06.20068882: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written consent was waived by Ethics Commission of TFPHJD due to the emergency of a major infectious disease.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were performed using SPSS (statistical package for social sciences) version 13.0 software (SPSS Inc.).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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

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  2. Version published to 10.1101/2020.05.06.20068882 on medRxiv