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J Glob Health . Characterization of demographic data, clinical signs, comorbidities, and outcomes according to the race in hospitalized individuals

tetano

Editor, Senior Moderator
J Glob Health


. 2022 Jul 25;12:05027.
doi: 10.7189/jogh.12.05027.
Characterization of demographic data, clinical signs, comorbidities, and outcomes according to the race in hospitalized individuals with COVID-19 in Brazil: An observational study


Nathália Ms Sansone[SUP] 1 2 [/SUP], Matheus N Boschiero[SUP] 1 2 [/SUP], Felipe E Valencise[SUP] 1 2 [/SUP], Camila Vc Palamim[SUP] 1 2 [/SUP], Fernando Al Marson[SUP] 1 2 [/SUP]



Affiliations

Abstract

Background: Brazil is a multiracial country with five major official races: White, Black, individuals with multiracial backgrounds, Asian, and Indigenous. Brazil is also one of the epicentres of the Coronavirus Disease (COVID)-19 pandemic. Thus, we evaluated how the races of the Brazilian population contribute to the outcomes in hospitalized individuals with COVID-19, and we also described the clinical profile of the five official Brazilian races.
Methods: We performed an epidemiological analysis for the first 67 epidemiological weeks of the COVID-19 pandemic in Brazil (from February 22, 2020, to April 04, 2021) using the data available at OpenDataSUS of the Brazilian Ministry of Health, a data set containing data from Brazilian hospitalized individuals. We evaluated more than 30 characteristics, including demographic data, clinical symptoms, comorbidities, need for intensive care unit and mechanical ventilation, and outcomes.
Results: In our data, 585 655 hospitalized individuals with a positive result in SARS-CoV-2 real-time chain reaction (RT-PCR) were included. Of these total, 309 646 (52.9%) identified as White, 31 872 (5.4%) identified as Black, 7108 (1.2%) identified as Asian, 235 108 (40.1%) identified as individuals with multiracial background, and 1921 (0.3%) identified as Indigenous. The multivariate analysis demonstrated that race was significative to predict the death being that Black (OR = 1.43; 95% CI = 1.39-1.48), individuals with multiracial background (OR = 1.36; 95% CI = 1.34-1.38), and Indigenous (OR = 1.91; 95% CI = 1.70-2.15) races were more prone to die compared to the White race. The Asian individuals did not have a higher chance of dying due to SARS-CoV-2 infection compared to White individuals (OR = 0.99; 95% CI = 0.94-1.06). In addition, other characteristics contributed as such as being male (OR = 1.17; 95% CI = 1.16-1.19), age (mainly, +85 years old - OR = 23.02; 95% CI = 20.05-26.42) compared to 1-year-old individuals, living in rural areas (OR = 1.22; 95% CI = 1.18-1.26) or in peri-urban places (OR = 1.25; 95% CI = 1.11-1.40), and the presence of nosocomial infection (OR = 1.91; 95% CI = 1.82-2.01). Among the clinical symptoms, the main predictors were dyspnoea (OR = 1.25; 95% CI = 1.23-1.28), respiratory discomfort (OR = 1.30; 95% CI = 1.28-1.32), oxygen saturation <95% (OR = 1.40; 95% CI = 1.38-1.43). Also, among the comorbidities, the main predictors were the presence of immunosuppressive disorder (OR = 1.44; 95% CI = 1.39-1.49), neurological disorder (OR = 1.21; 95% CI = 1.17-1.25), hepatic disorder (OR = 1.41; 95% CI = 1.34-1.50), diabetes mellitus (OR = 1.40; 95% CI = 1.37-1.42), cardiopathy (OR = 1.13; 95%CI = 1.11-1.14), hematologic disorder (OR = 1.34; 95% CI = 1.24-1.43), Down syndrome (OR = 1.61; 95% CI = 1.43-1.81), renal disease (OR = 1.15; 95% CI = 1.11-1.18), and obesity (OR = 1.18; 95% CI = 1.15-1.21). Individuals on intensive care unit (OR = 2.25; 95% CI = 2.22-2.29) and on invasive (OR = 10.92; 95% CI = 10.66-11.18) or non-invasive (OR = 1.33; 95% CI = 1.30-1.35) mechanical ventilation were more prone to die.
Conclusions: Alongside several clinical symptoms and comorbidities, we associated race with an enhanced risk of death in Black individuals, individuals with multiracial backgrounds, and Indigenous peoples.
 
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