Association between comorbidities and death from COVID-19 in different age groups

  1. Pedro Emanuel Fleitas
  2. María Cristina Almazán
  3. Sabrina Daniela Cortez
  4. Jorge Augusto Paz
  5. Rubén Oscar Cimino
  6. Alejandro Javier Krolewiecki

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Abstract

Background

This new COVID-19 pandemic challenges health systems around the world; therefore, it is extremely important to determine which patients with COVID-19 can evolve to more severe outcomes. Accordingly, we decided to assess the role that comorbidities play in death from COVID-19.

Methods

Two age groups (<60 and ≥ 60 years) were defined for analysis. Decision trees were made to identify which comorbidities had the highest fatality rate (FR). Multiple logistic regressions were performed to measure the association between comorbidities and death.

Results

A significant difference was found between the FR of <60 group and ≥ 60 group. The most frequent comorbidity were cardiac diseases and diabetes. The combination of comorbidities with the highest FR was diabetes with kidney disease. Combinations of more than two comorbidities presented higher FR. The comorbidities had higher Odd ratios in the younger group than in the older group.

Conclusions

Comorbidities seem to play a greater role in death from COVID-19 in the younger group, while in the> 60 group; age seems to be the most important factor. We assigned a score to the comorbidities and their combinations for both age groups to help the health personnel make decisions.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.12.21255365: (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 carried with RStudio version 1.3.1093
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    Figures were done with GraphPad Prime 9 Trial version (GraphPad Software Inc.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    It is important to understand the limitations of this study when interpreting these results. First, possible selection biases cannot be ruled out due to the reduction of the data file. Second, the data come from all the states of Brazil, but might not be representative of the entire population, and the generalizability of the results beyond this cohort is unclear. However, it is worth noting the high number of cases analyzed and that the proportion of the comorbidities in the database (n=549733) is similar to in the original data file (n=8056794). In conclusion, we demonstrate that diabetes, kidney disease, respiratory disease, cardiovascular disease, and immunosuppression are risk factors related to death from COVID-19, where age seems to be a determining factor. The combination of comorbidities increases the risk, which must be considered and analyzed for clinical decisions.

    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 10.1101/2021.04.12.21255365v1 on medRxiv