What question did this study set out to answer?

The study aimed to identify factors predicting worsening disease and COVID-19 related deaths using genomic, clinical, and epidemiological data.

March 17, 2026The Brazilian Journal of Infectious Diseases0 citationsOpen Access

Evaluation of Covid-19–associated Mortality Based on Genomic, Clinical, and Epidemiological Data: A Retrospective Cohort Study in a Tertiary Public Hospital.

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YOYasmim Colins Silva de OliveiraUniversidade de Ribeirão Preto MSMichel Morais Marques SawanUniversidade de Ribeirão Preto GCGuilherme Silveira CastroUniversidade de Ribeirão Preto

Key Points

The study aimed to identify factors predicting worsening disease and COVID-19 related deaths using genomic, clinical, and epidemiological data.
Retrospective cohort analysis of 2,395 samples from COVID-19 positive patients.
Collection of clinical, epidemiological, and genomic data including demographics, disease severity, and hospitalization details.
Logistic regression analysis to determine association of variables with mortality.
1,943 patients (81.1%) had mild to moderate symptoms, while 210 (8.8%) had critical disease.
Age and underlying neoplasms were strongly associated with increased mortality risk.
Vaccination and being a healthcare worker were identified as protective factors against death.

Abstract

The public health emergency caused by the SARS-CoV-2 pandemic resulted in a high number of severe cases and deaths. This study aimed to evaluate clinical, epidemiological, and genomic aspects related to COVID-19, in order to identify factors that may predict the risk of disease worsening and COVID-19–related death. This retrospective cohort study evaluated nasopharyngeal and/or oropharyngeal secretion samples from patients with positive real-time RT-PCR results for SARS-CoV-2, treated at a tertiary public university hospital between April 4, 2020, and January 31, 2022. Samples with Ct values ≤30 were selected and fully sequenced. A total of 2,395 distinct samples corresponding to 2,379 patients were obtained. Complementary information—such as personal and epidemiological history, clinical manifestations, length of hospital stay, ICU requirement, and disease severity—was collected from electronic medical records and Epidemiological Surveillance data to analyze the final outcome (recovery or death). Among the 2,395 patients, 1,943 (81.1%) presented mild to moderate symptoms, 206 (8.6%) severe disease, and 210 (8.8%) critical disease. A total of 656 patients (27.4%) required hospitalization, and 282 (11.7%) required ICU admission, with a mean ICU stay of 14.5 days. Of the patients, 1,469 (61.3%) were female and 926 (38.7%) male. The mean age was 42.2 years among survivors and 63.3 years among those who died. The Original strain accounted for 923 infections (38.3%), followed by the Gamma genotype with 773 cases (30%), which was the most strongly associated with death (12.8%). Multivariate logistic regression analysis identified age (OR 1045.566; 95% CI 1032.739–1058.552), neoplasms (OR 2.55; 95% CI 1.408–4.638), and clinical presentation (OR 3169.781; 95% CI 1723.513–5829.669) as relevant variables associated with death. Vaccination (OR 0.704; 95% CI 0.524–0.948) and being a healthcare worker (OR 0.088; 95% CI 0.025–0.302) behaved as protective factors for the primary outcome. The data show that advanced age, underlying neoplasms, and more severe COVID-19 cases were more strongly associated with death. Conversely, being a hospital employee and vaccination were protective factors against the worst outcome. These findings are useful for COVID-19 case management.

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Cite This Study

Oliveira et al. (2026) studied this question.

synapsesocial.com/papers/69b8ef36deb47d591b8c53d0 https://doi.org/https://doi.org/10.1016/j.bjid.2026.105287

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