Article ; Online: Sex, Age, and Comorbidities Are Associated with SARS-CoV-2 Infection, COVID-19 Severity, and Fatal Outcome in a Mexican Population
Journal of Clinical Medicine, Vol 12, Iss 2676, p
A Retrospective Multi-Hospital Study
2023 Volume 2676
Abstract: People with comorbidities and the male sex are at a higher risk of developing severe COVID-19. In the present study, we aim to investigate the associated factors for infection, severity, and death due to COVID-19 in a population from Nuevo León, México. ... ...
Abstract | People with comorbidities and the male sex are at a higher risk of developing severe COVID-19. In the present study, we aim to investigate the associated factors for infection, severity, and death due to COVID-19 in a population from Nuevo León, México. Epidemiological COVID-19 data were collected from 65 hospitals from December 2020 to May 2022. A total of 75,232 cases were compiled from which 25,722 cases were positive for SARS-CoV-2. Male sex, older age, diabetes, obesity, and hypertension were associated with infection. In addition to the above-mentioned factors, renal disease, cardiovascular disease, and immunosuppression were found to be associated with increased COVID-19 severity. These factors, as well as neurological diseases, are also associated with death due to COVID-19. When comparing the different variants of SARs-CoV-2, the variant B1.1.519 increased the probability of death by 2.23 times compared to the AY.20 variant. Male sex, older age, diabetes, obesity, and hypertension are associated with SARS-CoV-2 infection, severity, and death. Along with the aforementioned comorbidities, renal disease, cardiovascular disease, and immunosuppression are also associated with severity and death. Another factor associated with death is the presence of neurological disease. The SARS-CoV-2 B1.1.519 variant increases the odds of death compared to the SARS-CoV-2 AY.20 variant. |
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Keywords | COVID-19 ; SARS-CoV-2 ; association ; severity ; death ; Mexico ; Medicine ; R |
Subject code | 610 |
Language | English |
Publishing date | 2023-04-01T00:00:00Z |
Publisher | MDPI AG |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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