The impact of COVID-19 in diabetic kidney disease and chronic kidney disease: A population-based study

  1. Juan A. Leon-Abarca
  2. Roha S. Memon
  3. Bahar Rehan
  4. Maimoona Iftikhar
  5. Antara Chatterjee

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Abstract

Background

The spectrum of pre-existing renal disease is known as a risk factor for severe COVID-19 outcomes. However, little is known about the impact of COVID-19 on patients with diabetic nephropathy in comparison to patients with chronic kidney disease.

Methods

We used the Mexican Open Registry of COVID-19 patients 11 to analyze anonymized records of those who had symptoms related to COVID-19 to analyze the rates of SARS-CoV-2 infection, development of COVID-19 pneumonia, admission, intubation, Intensive Care Unit admission and mortality. Robust Poisson regression was used to relate sex and age to each of the six outcomes and find adjusted prevalences and adjusted prevalence ratios. Also, binomial regression models were performed for those outcomes that had significant results to generate probability plots to perform a fine analysis of the results obtained along age as a continuous variable.

Results

The adjusted prevalence analysis revealed that that there was a a 87.9% excess probability of developing COVID-19 pneumonia in patients with diabetic nephropathy, a 5% excess probability of being admitted, a 101.7% excess probability of intubation and a 20.8% excess probability of a fatal outcome due to COVID-19 pneumonia in comparison to CKD patients (p< 0.01).

Conclusions

Patients with diabetic nephropathy had nearly a twofold rate of COVID-19 pneumonia, a higher probability of admission, a twofold probability of intubation and a higher chance of death once admitted compared to patients with chronic kidney disease alone. Also, both diseases had higher COVID-19 pneumonia rates, intubation rates and case-fatality rates compared to the overall population.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.12.20193235: (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
    The data was analyzed through the STATA 14 program considering a p value of 0.05 as the statistically significant threshold.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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:
    Few limitations should be considered. In view of the publicly available data, we could not have access to patients’ clinical records including laboratory test reports. Thus, the severity of the underlying kidney disease could not be taken into consideration in the study. Due to similar reasons, it was unclear if patients received treatment for diabetes or were under any kind of renal replacement therapy. Secondly, given the observational nature of our study, the associations found may not be causal. Although we were able to adjust for multiple confounding factors, we cannot rule out unmeasured or residual confounding. Furthermore, a limited number of studies have assessed the clinical picture of COVID-19 in patients with diabetic nephropathy, conducted in a few countries only. Thus, a detailed comparison and contrast could not be drawn between the findings of our study and those previously conducted. Other than a few hypotheses on the poorer COVID-19 endpoints, our study did not aim to portray a robust clinical picture of COVID-19 outcomes in cases with multiple comorbid conditions. Our manuscript calls for further research in this area as we conclude alarming findings. The greater severity of the COVID-19 disease course in CKD and diabetic nephropathy patients is then confirmed albeit the pure clinical and laboratorial picture remains unclear. Future research in other settings could help fill these gaps in the knowledge and would help formulate guidelines of care in these co...

    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 10.1101/2020.09.12.20193235v1 on medRxiv