Profile of SARS-CoV-2/HIV-1 coinfection in patients from the extreme south of Brazil

The COVID-19 pandemic, caused by SARS-CoV-2, has resulted in millions of infections and deaths. Studies describing the pathophysiology and characterizing the outcome of the disease in specific populations, including those living with HIV, are necessary. There is no consensus on whether the disease worsens in immunosuppressed patients, which is considered a risk factor, or if immunosuppression might confer protection against cytokine storms. This retrospective descriptive study reports on the profile of SARS-CoV-2/HIV-1 coinfection in individuals seeking care at the Miguel Riet Correa Jr. University Hospital, located in the southernmost part of Brazil, between January 2020 and December 2022. During this period, 363 HIV-positive individuals sought diagnostic services for COVID-19, with 50 (13.7%) testing positive for the novel coronavirus. Among the 363 patients tested, the average age was 42.7 years, and 50.4% were female. For those with coinfection, several variables were analyzed, revealing a predominantly female population (62%), with 60% of white skin color and an average age of 47.8 years. Among these individuals, 48% exhibited symptoms characteristic of COVID-19, 40% had some comorbidity or coinfection, and 32% required hospitalization. Among the hospitalized patients who were discharged, 55% had discontinued HIV treatment, and among those not adhering to antiretroviral therapy (ART), 66.7% died from COVID-19. The average hospital stay observed was 24 days, and 41.2% of patients required supplementary oxygen. Conversely, among patients who did not require hospitalization, 95% were on ART. These findings are consistent with other studies, suggesting that the course of COVID-19 in people living with HIV is similar to that in the general population, with attention to comorbidities as a risk factor in this group. It may be suggested that maintaining HIV treatment adherence could be protective against COVID-19 hospitalization (p = 0.002). Prevalence testing and Chi-square tests were used for data analysis to observe the correlation between hospitalization and discharge outcomes when considering the use of antiretroviral therapy for HIV treatment.