Meta-analysis of COVID-19 patients to understand the key predictors of mortality in the non-vaccinated groups in remote settings

  1. Neha L. Jain
  2. Karishma Parekh
  3. Rishi Saigal
  4. Amal Alyusuf
  5. Gabrielle Kelly
  6. Alokkumar Jha

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Abstract

Various studies have looked into the impact of the COVID-19 vaccine on large populations. However, very few studies have looked into the remote setting of hospitals where vaccination is challenging due to social structure, myths, and misconceptions. There is a consensus that elevated inflammatory markers such as CRP, ferritin, D-dimer correlate with increased severity of COVID-19 and are associated with worse outcomes. In the present study, through retrospective meta-analysis, we have looked into ∼20 months of SARS-COV2 infected patients with known mortality status and identified predictors of mortality concerning their comorbidities, various clinical parameters, inflammatory markers, superimposed infections, length of hospitalization, length of mechanical ventilation and ICU stay. Studies with larger sample sizes have covered the outcomes through epidemiological, social, and survey-based analysis—however, most studies cover larger cohorts from tertiary medical centers. In the present study, we assessed the outcome of non-vaccinated COVID 19 patients in a remote setting for 20 months from January 1, 2020, to August 30, 2021, at CHI Mercy Health in Roseburg, Oregon. We also included two vaccinated patients from September 2021 to add to the power of our cohort. The study will provide a comprehensive methodology and deep insight into multi-dimensional data in the unvaccinated group, translational biomarkers of mortality, and state-of-art to conduct such studies in various remote hospitals.

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  1. Version published to 10.1101/2022.01.04.21267659v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2022.01.04.21267659: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisPower calculation: The sample size of 38 patients (32 Vaccinated, 5 Unvaccinated, 1 Unknown) accrued as of August 2021 yields 80% power at an alpha of 0.05 to detect a hazard ratio of 0.01 for severe COVID-19, assuming two unequally matched groups.

    Table 2: Resources

    No key resources detected.

    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:
    Although this study was able to identify critical biomarkers for severe COVID 19 patients, it also has some limitations. This being a retrospective analysis, the findings are primarily used in generating hypotheses, not necessarily in clinical practice. Furthermore, as a registry analysis, there is an inherent bias in the patient selection determined by registry entrant decided based on pre-defined criteria such as outcome in our case. Consequently, the study population likely has a higher COVID 19 severity than the general population of cancer patients with COVID 19. Additionally, as discussed above, this study included a more significant proportion of unvaccinated patients than other analyses, and this may have led to improved generalizability reflecting the impact of COVID 19 in remote settings. However, to maximize sample size, a small number of vaccinated patients were added to the cohort, limiting the generalizability of the findings. Additionally, there are significant differences between the timing of COVID 19 diagnosis in this study and the epidemiology of the pandemic in the general population, with an overrepresentation of diagnoses in the early part of the pandemic period. In all likelihood, this study does not include patients with delta-variant since it includes data up until the third trimester of 2021. In light of the ordinal outcome of COVID 19 severity, including metrics such as hospitalization and ICU admission, patients without vaccination may have an adva...

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2022.01.04.21267659v1 on medRxiv