Analysis of early renal injury in COVID-19 and diagnostic value of multi-index combined detection

  1. Xu-wei Hong
  2. Ze-pai Chi
  3. Guo-yuan Liu
  4. Hong Huang
  5. Shun-qi Guo
  6. Jing-ru Fan
  7. Xian-wei Lin
  8. Liao-zhun Qu
  9. Rui-lie Chen
  10. Ling-jie Wu
  11. Liang-yu Wang
  12. Qi-chuan Zhang
  13. Su-wu Wu
  14. Ze-qun Pan
  15. Hao Lin
  16. Yu-hua Zhou
  17. Yong-hai Zhang

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Abstract

Objectives

The aim of the study was to analyze the incidence of COVID-19 with early renal injury, and to explore the value of multi-index combined detection in diagnosis of early renal injury in COVID-19.

Design

The study was an observational, descriptive study.

Setting

This study was carried out in a tertiary hospital in Guangdong, China.

Participants

12 patients diagnosed with COVID-19 from January 20, 2020 to February 20, 2020.

Primary and secondary outcome measures

The primary outcome was to evaluate the incidence of early renal injury in COVID-19. In this study, the estimated glomerular filtration rate (eGFR), endogenous creatinine clearance (Ccr) and urine microalbumin / urinary creatinine ratio (UACR) were calculated to assess the incidence of early renal injury. Secondary outcomes were the diagnostic value of urine microalbumin (UMA), α1-microglobulin (A1M), urine immunoglobulin-G (IGU), urine transferring (TRU) alone and in combination in diagnosis of COVID-19 with early renal injury.

Results

While all patients had no significant abnormalities in serum creatinine (Scr) and blood urea nitrogen (BUN), the abnormal rates of eGFR, Ccr, and UACR were 66.7%, 41.7%, and 41.7%, respectively. Urinary microprotein detection indicated that the area under curve (AUC) of multi-index combined to diagnose early renal injury in COVID-19 was 0.875, which was higher than UMA (0,813), A1M (0.813), IGU (0.750) and TRU (0.750) alone. Spearman analysis showed that the degree of early renal injury was significantly related to C-reactive protein (CRP) and neutrophil ratio (NER), suggesting that the more severe the infection, the more obvious the early renal injury. Hypokalemia and hyponatremia were common in patients with COVID-19, and there was a correlation with the degree of renal injury.

Conclusions

Early renal injury was common in patients with COVID-19. Combined detection of UMA, A1M, IGU, and TRU was helpful for the diagnosis of early renal injury in COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.07.20032599: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were processed using SPSS 25.0 statistical software.
    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

    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 10.1101/2020.03.07.20032599v2 on medRxiv
  3. Version published to 10.1101/2020.03.07.20032599v1 on medRxiv