Julio Ancochea1,2,3, Jose L Izquierdo4,5, Joan B Soriano1,2,3. 1. Department of Respiratory Medicine, Hospital Universitario de La Princesa, Madrid, Spain. 2. Department of Respiratory Medicine, Universidad Autónoma de Madrid, Madrid, Spain. 3. Centro de Investigación en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 4. Department of Respiratory Medicine, Universidad de Alcalá, Madrid, Spain. 5. Department of Respiratory Medicine, Hospital Universitario de Guadalajara, Guadalajara, Spain.
Abstract
Background: The impact of sex and gender in the incidence and severity of coronavirus disease 2019 (COVID-19) remains controversial. Here, we aim to describe the characteristics of COVID-19 patients at disease onset, with special focus on the diagnosis and management of female patients with COVID-19. Methods: We explored the unstructured free text in the electronic health records (EHRs) within the SESCAM Healthcare Network (Castilla La-Mancha, Spain). The study sample comprised the entire population with available EHRs (1,446,452 patients) from January 1st to May 1st, 2020. We extracted patients' clinical information upon diagnosis, progression, and outcome for all COVID-19 cases. Results: A total of 4,780 patients with a confirmed diagnosis of COVID-19 were identified. Of these, 2,443 (51%) were female, who were on average 1.5 years younger than male patients (61.7 ± 19.4 vs. 63.3 ± 18.3, p = 0.0025). There were more female COVID-19 cases in the 15-59-year-old interval, with the greatest sex ratio (95% confidence interval) observed in the 30-39-year-old range (1.69; 1.35-2.11). Upon diagnosis, headache, anosmia, and ageusia were significantly more frequent in females than males. Imaging by chest X-ray or blood tests were performed less frequently in females (65.5% vs. 78.3% and 49.5% vs. 63.7%, respectively), all p < 0.001. Regarding hospital resource use, females showed less frequency of hospitalization (44.3% vs. 62.0%) and intensive care unit admission (2.8% vs. 6.3%) than males, all p < 0.001. Conclusion: Our results indicate important sex-dependent differences in the diagnosis, clinical manifestation, and treatment of patients with COVID-19. These results warrant further research to identify and close the gender gap in the ongoing pandemic.
Background: The impact of sex and gender in the incidence and severity of coronavirus disease 2019 (COVID-19) remains controversial. Here, we aim to describe the characteristics of COVID-19patients at disease onset, with special focus on the diagnosis and management of female patients with COVID-19. Methods: We explored the unstructured free text in the electronic health records (EHRs) within the SESCAM Healthcare Network (Castilla La-Mancha, Spain). The study sample comprised the entire population with available EHRs (1,446,452 patients) from January 1st to May 1st, 2020. We extracted patients' clinical information upon diagnosis, progression, and outcome for all COVID-19 cases. Results: A total of 4,780 patients with a confirmed diagnosis of COVID-19 were identified. Of these, 2,443 (51%) were female, who were on average 1.5 years younger than male patients (61.7 ± 19.4 vs. 63.3 ± 18.3, p = 0.0025). There were more female COVID-19 cases in the 15-59-year-old interval, with the greatest sex ratio (95% confidence interval) observed in the 30-39-year-old range (1.69; 1.35-2.11). Upon diagnosis, headache, anosmia, and ageusia were significantly more frequent in females than males. Imaging by chest X-ray or blood tests were performed less frequently in females (65.5% vs. 78.3% and 49.5% vs. 63.7%, respectively), all p < 0.001. Regarding hospital resource use, females showed less frequency of hospitalization (44.3% vs. 62.0%) and intensive care unit admission (2.8% vs. 6.3%) than males, all p < 0.001. Conclusion: Our results indicate important sex-dependent differences in the diagnosis, clinical manifestation, and treatment of patients with COVID-19. These results warrant further research to identify and close the gender gap in the ongoing pandemic.
Entities:
Keywords:
COVID-19; SARS-CoV-2; artificial intelligence; natural language processing; sex differences
Authors: Rachel Harwood; Helen Yan; Nishanthi Talawila Da Camara; Clare Smith; Joseph Ward; Catrin Tudur-Smith; Michael Linney; Matthew Clark; Elizabeth Whittaker; Defne Saatci; Peter J Davis; Karen Luyt; Elizabeth S Draper; Simon E Kenny; Lorna K Fraser; Russell M Viner Journal: EClinicalMedicine Date: 2022-02-11
Authors: Jose M Celaya-Padilla; Karen E Villagrana-Bañuelos; Juan José Oropeza-Valdez; Joel Monárrez-Espino; Julio E Castañeda-Delgado; Ana Sofía Herrera-Van Oostdam; Julio César Fernández-Ruiz; Fátima Ochoa-González; Juan Carlos Borrego; Jose Antonio Enciso-Moreno; Jesús Adrián López; Yamilé López-Hernández; Carlos E Galván-Tejada Journal: Diagnostics (Basel) Date: 2021-11-25