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<dc:title>Development of a Risk Predictive Model for Erectile Dysfunction at 12 Months after COVID-19 Recovery: A Prospective Observational Study</dc:title>
<dc:creator>Natal Alvarez, Fernando</dc:creator>
<dc:creator>Conde Redondo, María Consuelo</dc:creator>
<dc:creator>Sierrasesumaga Martin, Nicolás</dc:creator>
<dc:creator>García Viña, Alejandro</dc:creator>
<dc:creator>Marfil Peña, Carmen</dc:creator>
<dc:creator>Bahillo Martínez, Alfonso</dc:creator>
<dc:creator>Jojoa Acosta, Mario Fernando</dc:creator>
<dc:creator>Tamayo Gómez, Eduardo</dc:creator>
<dc:subject>COVID-19</dc:subject>
<dc:subject>erectile dysfunction</dc:subject>
<dc:subject>cardiovascular disease</dc:subject>
<dc:subject>post-acute COVID-19 syndrome</dc:subject>
<dc:subject>logistic models</dc:subject>
<dc:description>Producción Científica</dc:description>
<dc:description>Objectives: To develop a risk prediction model for the identification of features involved in the prediction of erectile dysfunction (ED) at 12 months following COVID-19 recovery. Methods: We performed an observational prospective multicentre study. Participants were classified according to their history of COVID-19: (I) patients with a past history of COVID-19 and (II) patients without a previous microbiological diagnosis of COVID-19. A total of 361 patients (past history of COVID-19, n = 166; no past history of COVID-19, n = 195) were assessed from January 2022 to March 2023. Patients with a past history of COVID-19 were assessed at 12 months following COVID-19 recovery. The primary outcome measure was ED, assessed through the 5-item International Index of Erectile Function (IIEF-5). Data concerning epidemiologic variables, comorbidities and active treatment were also collected. We performed a binary logistic regression to develop a risk predictive model. Among the models developed, we selected the one with the higher Area Under the Curve (AUC). Results: The median age was 55 years in both groups. The ED prevalence was 55.9% in patients with past history of COVID-19 and 44.1% in those with no past history of COVID-19. The best predictive model developed for ED comprised 40 variables and had an AUC of 0.8. Conclusions: We developed a regression model for the prediction of ED 12 months after COVID-19 recovery. The application of our predictive tool in a community setting could eventually prevent the adverse effects of ED on cardiovascular health and the associated unfavourable economic impact.</dc:description>
<dc:description>Instituto de Salud Carlos III (proyecto PI21/00917, PI18/01238, CIBERINFEC CB21/13/00051)</dc:description>
<dc:description>Junta de Castilla y León (proyecto GRS 2546/A/22, GRS  2425/A/21, GRS 1922/A/19, GRS 2057/A/19)</dc:description>
<dc:description>Consejería de Educación de Castilla y León (proyecto VA256P20)</dc:description>
<dc:description>Fundación Ramón Areces (proyecto CIVP19A5953)</dc:description>
<dc:date>2025-12-01T08:17:32Z</dc:date>
<dc:date>2025-12-01T08:17:32Z</dc:date>
<dc:date>2024</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:identifier>Journal of Clinical Medicine, 2024, vol. 13, n. 19. p. 5757</dc:identifier>
<dc:identifier>2077-0383</dc:identifier>
<dc:identifier>https://uvadoc.uva.es/handle/10324/80181</dc:identifier>
<dc:identifier>10.3390/jcm13195757</dc:identifier>
<dc:identifier>5757</dc:identifier>
<dc:identifier>19</dc:identifier>
<dc:identifier>Journal of Clinical Medicine</dc:identifier>
<dc:identifier>13</dc:identifier>
<dc:identifier>2077-0383</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>https://www.mdpi.com/2077-0383/13/19/5757</dc:relation>
<dc:rights>Atribución 4.0 Internacional</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:format>application/pdf</dc:format>
<dc:publisher>Multidisciplinary Digital Publishing Institute</dc:publisher>
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<europeana:rights>http://creativecommons.org/licenses/by/4.0/</europeana:rights>
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