Andres Felipe Valencia Rendon et al. Isabela Mendes Volschan Manoella Novais Pereira Wagner Lima Monteiro … Alessandra de Freitas Pimentel Emilia Matos do Nascimento Basilio de Bragança Pereira Glaucia Maria Moraes de Oliveira
Abstract
Background
Brazil had high COVID-19 lethality/mortality with multiple social inequalities, where color/race was highly relevant, especially in Rio de Janeiro. Therefore, we hypothesize that COVID-19 hospitalized patients with a highly socially vulnerable background would have more significant in-hospital mortality.
Objective
To analyze the socioeconomic factors of social vulnerability and their association with COVID-19 mortality.
Methods
This work was a prospective study of 274 confirmed adult COVID-19 hospitalized patients in the University Hospital of Clementino Fraga Filho (HUCFF). The clinical features/blood chemistry information were collected from the clinical record. The ArcGIS Pro Software (Esri Gis mapping software, Redlands California-US) and a Python-based algorithm were used to determine in-app/in-map variable management relevance to the socioeconomic variables, inequity markers, and vulnerability. Our study also analyzed the transfers from other primary care institutions to our hospital in order to examine its potential delays in advanced medical care. Logistic regression and ROC curve were used to investigate in-hospital mortality for our statistical analysis. The significance level adopted in the statistical analysis was 5% Results: Male sex, total days of hospitalization, age, having more than three comorbidities, intensive care unit (ICU) admission, hemodialysis, and transfer from other hospitals showed statistical significance. Patients living in low-adequate households (p = 0.030) with high in-house individual agglomeration markers (p = 0.017) and transfers from another Primary Health Care (PHC) institution (p = 0.047) were associated with increased in-hospital mortality, with high ICU admission and mechanical ventilation.
Conclusions
In-hospital mortality due to COVID-19 was influenced by social individual background characteristics of vulnerability. Among other clinical parameters, these markers should be considered to predict the likelihood of complications related to the COVID-19 pandemic.