Characteristics of lymphocyte subsets and their predicting values for the severity of COVID-19 patients

  1. Jingrong Wang
  2. Xingqi Dong
  3. Boting Zhang
  4. Xinping Yang
  5. Zhi Li
  6. Xicheng Wang
  7. Shuguang Zuo

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Abstract

Severe COVID-19 patients showed worse clinical outcomes compared to mild and moderate patients. However, effective indicators are still lacking to predict the severity of the disease. In the present study, we retrospectively analyzed the clinical and laboratory data of 16 COVID-19 patients and found that the absolute counts of three T-cells (CD3 + , CD4 + , and CD8 + ) were significantly lower in the moderate and severe patients than those in mild patients and were significantly lower in severe patients than in moderate patients on admission. With the recovery of the COVID-19, serum levels of inflammatory biomarkers (CRP, PCT, and IL6) of moderate and severe patients gradually decreased. In contrast, the counts of lymphocytes and their subsets including CD3 + , CD4 + , and CD8 + T cells gradually increased in severe patients, and eventually showed comparable levels with moderate patients. ROC analysis showed that the counts of CD3 + , CD4 + , and CD8 + T-cells with AUC > 0.9 have potential values for predicting the severity of COVID-19 patients. In conclusion, the reduction of CD3 + , CD4 + , and CD8 + T-cells is related to the severity of COVID-19 and dynamic detection of these T-lymphocyte subsets may help predict the outcome of the patients.

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    SciScore for 10.1101/2020.05.01.20086421: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data collection: The study was approved by the Ethics Committee of Yunnan Provincial Hospital of Infectious Disease, AIDS Care Center.
    Consent: Oral consent was obtained from patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Flow cytometry was performed on FACSCalibur (BD Biosciences, USA).
    FACSCalibur
    suggested: None
    Mild patients: the clinical symptoms of patients are mild, and there is no pneumonia on CT imaging.
    Mild
    suggested: (MILD, RRID:SCR_003335)
    The ggplot2 package (Version 3.2.1, http://ggplot2.tidyverse.org, https://github.com/tidyverse/ggplot2) was used to visualize data with R.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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 10.1101/2020.05.01.20086421v2 on medRxiv
  3. Version published to 10.1101/2020.05.01.20086421v1 on medRxiv