Hyperinflammatory conditions, gender differences and mortality in Indian COVID-19 patients

  1. Fouzia Shoeb
  2. Imran Hussain
  3. Gazala Afrin
  4. Shagufta T. Mufti
  5. Tabrez Jafar
  6. Syed T. Raza
  7. Farzana Mahdi

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Purpose

Evidence suggests that COVID-19 induces hyperinflammatory conditions and causes relatively more deaths in males than females. The purpose of this study was to analyze gender differences associated with various hyperinflammatory conditions (HIC) and mortality in the Indian COVID-19 patients

Methods

This study was conducted at the Era’s Lucknow Medical College and Hospital (ELMCH), ERA University, which is located in the northern part of India. Starting from July 4, 2020 till December 3, 2020 a total of 2997 patients were treated at ELMCH. We randomly collected blood samples from 150 severe COVID-19 patients (required oxygen) between August 10 and September 15, 2020 for analyzing the following HIC and associated laboratory markers: hyperferritinaemia (serum ferritin), hematological dysfunctions (lymphocytopenia and neutrophil to lymphocyte ratio), cytokinaemia (C-reactive protein), coagulopathy (D-dimer), liver inflammation (aspartate aminotransferase), renal inflammation (blood urea and creatinine), and hyperglycemia (random blood glucose). The threshold values/cut off limits of these laboratory markers used for analyzing the risk of mortality in male and female COVID-19 patients were set according to the scale validated recently by Webb et al, (2020).

Results

In the above cohort of consecutively admitted COVID-19 patients, analysis of various HIC revealed hyperferritinaemia (odd ratio: 2.9, 95% CI 1.4-6.0), hematological dysfunctions (odd ratio: 2.10, 95% CI 1.0-4.2), hepatic inflammation (odd ratio: 2.0, 95% CI 0.52-7.40), and coagulopathy (odd ratio: 1.5, 95% CI 1.50, 95% CI 0.50-4.60) were more prevalent and sever in male COVID-19 patients. Approximately 86% male to 64% female COVID-19 patients developed lymphocytopenia. Regarding mortality, while hyperferritinaemia (odd ratio: 1.70, 95% CI 0.37-7.43) and cytokinaemia (odd ratio: 1.60, 95% CI 0.37 −7.30) were strongly associated with mortality in male COVID-19 patients, coagulopathy (odd ratio: 3.30, 95% CI 0.31-35), and hematological dysfunctions (odd ratio: 1.70, 95% CI 0.27-10) were more commonly associated with mortality in female COVID-19 patients. Nearly 80% male and female COVID-19 patients, who died had developed ≥2 criteria of HIS criteria. Chronic renal disease was associated with more deaths in female than male COVID-19 patients (odd ratio: 2.0, 95% CI 0.54 - 7.4). While the mortality proportion was slightly higher in male (6.3%) than female (4.5%) COVID-19 patients, survival curves of the two genders were not different (hazard ratio: 1.02, 95% CI 0.71-1.40, P = 0. 953).

Conclusion

Distinct HIC were associated with the severity, and mortality in male and female COVID-19 patients. Coagulopathy and renal injury were detrimental, specifically, for female COVID-19 patients. The overall mortality proportion was around 5.3%. The above results suggest that gender differences associated with COVID-19 severity and mortality arise due to differences in various HIC. These results may help in developing personalized or gender based treatments for COVID-19 patients.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.01.19.21250134: (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
    Statistical analyses: Prism (GraphPad) was used for performing various statistical analyses.
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    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: 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 10.1101/2021.01.19.21250134 on medRxiv