Prevalent comorbidities among young and underprivileged: Death portrait of COVID-19 among 235 555 hospitalized patients in Brazil

  1. Eduardo Pietre
  2. Gabriel Pessanha Amorim
  3. Maria Fernanda Bittencourt
  4. Marcelo Ribeiro-Alves
  5. Mariana Acquarone

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Background COVID 19 has been alarmingly spreading worldwide, with Brazil ranking third in total number of cases and second in deaths. Being a continental country, which comprises many ethnic groups and an engrained social inequality, the pandemic evidenced this heterogeneous discrepancy. We aimed to estimate the impact of associated risk factors, isolated or combined, on COVID 19 severeness, detecting specific epidemiological profiles for multiple age ranges in hospitalized Brazilians. Methods In this large retrospective cohort study, we used open-access data from the Ministry of Health of Brazil with COVID 19 confirmed hospitalized patients annotated in SRAG system between February and August 2020, a total of 235555 entries. The association of COVID 19 death with socio-demographic and clinical characteristics was analysed and presented as odds ratios adjusted by confounding co-variables. We also presented marginal mean aOR values for high-order interactions either by or not another fixed level or condition. We kept all other variables in the multivariate logistic models in their mean values or equal proportions. Findings Younger individuals with one or more comorbidities had an adjusted odds ratio up to four-fold compared to those without it, in the same age interval. Younger diabetic patients either self-declared as brown ethnicity (aOR 5,58, 95% CI 4,97-6,25; p < 0,0001) or with some other associated comorbidities, mainly chronic hematologic disease (21,09, 13,64-32,6; p < 0,0001) and obesity (aOR 21,7, 95% CI not calculated; p < 0,0001), resulted in outstanding death risk. Age over 60, particularly over 90 (28,91, 24,5-34,11; p < 0,001), usage of invasive ventilatory support (16,23, 14,05-18,75; p < 0,001), admission to intensive care units (3,14, 2,82-3,48; p < 0,001), multiple respiratory symptoms (3,24, 2,79-3,75; p < 0,0001), black ethnicity (1,78, 1,52-2,07; p < 0,05), and diagnosis previous to hospitalization (1,32, 1,19-1,47; p < 0,05) were associated with higher death odds. As protective factors, with roughly one third less death risk, we found hospitalization duration of (4, 7] days and illness onset to hospitalization over 6 days. Interpretation We found evidence for increased COVID 19 risk in two distinct groups: younger patients with prevalent comorbidities, especially in brown ethnicity, and patients with black ethnicity. We speculate that the pro-inflammatory synergism of COVID 19 and comorbidities, promoting an overproduction of cytokines, is partially the cause of higher mortality in this young group. Brazilian black and brown are underprivileged populations, with structural social inequality, limited healthcare access and, thus, remarkable disease vulnerability. Our study supplies essential data to patient stratification upon admission, optimizing hospital management, and to guide public policy determinations, including group prioritization for COVID 19 vaccination in Brazil.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.01.22.21250346: (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

    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:
    Our study has some key limitations, mainly regarding data quality, annotation accuracy, suspected under-reported data, and lack of government open-access information of non-hospitalized patients in Brazil. This is a relevant bias as studies based only on hospitalized patients are focused on more severe cases and fatalities. Furthermore, we cannot guarantee that missing information is not subject to bias. Although extensive, some fundamental information that greatly affects the prognosis of the disease is missing in the SRAG form, mainly regarding smoking, alcohol intake, oncological disorders, and chronic high blood pressure.39–42 As for our study’s relevance, drawing attention to diabetes, lack of reliable data on Body Mass Index (BMI) prevented us from differentiating the impact of obesity and severe obesity in mortality. This is mainly important because obesity is a chronic inflammatory condition associated with cardiometabolic and immune dysfunction, increased risk of diabetes and hematological disease, leading patients to be more susceptible to develop severe forms of COVID-19.36 The under-reporting in the BMI may be aggravated due to professionals being not properly instructed on how to use and fill out the form items. Thus, we suggest remodeling the form, together with better orientation on how to deal with information gathering. Nonetheless, despite all Brazilian health system challenges, the average notification delay was 0 days (IQR=2), demonstrating high efficiency...

    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 10.1101/2021.01.22.21250346 on medRxiv