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dc.contributor.authorGutierrez Tobal, Gonzalo César 
dc.contributor.authorGómez Pilar, Javier 
dc.contributor.authorFerreira Santos, Daniela
dc.contributor.authorPereira Rodrigues, Pedro
dc.contributor.authorÁlvarez González, Daniel 
dc.contributor.authorCampo Matias, Félix del 
dc.contributor.authorGozal, David
dc.contributor.authorHornero Sánchez, Roberto 
dc.date.accessioned2025-12-23T11:13:12Z
dc.date.available2025-12-23T11:13:12Z
dc.date.issued2026
dc.identifier.citationComputer Methods and Programs in Biomedicine, 2026, vol. 275, p. 109209es
dc.identifier.issn0169-2607es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/81016
dc.descriptionProducción Científicaes
dc.description.abstractBackground and objectives: Timely treatment of pediatric obstructive sleep apnea (OSA) can prevent or reverse neurocognitive and cardiovascular morbidities. However, whether distinct phenotypes exist and account for divergent treatment effectiveness remains unknown. In this study, our goal is threefold: i) to define new data- driven pediatric OSA phenotypes, ii) to evaluate possible treatment effectiveness differences among them, and iii) to assess phenotypic information in predicting OSA resolution. Methods: We involved 22 sociodemographic, anthropometric, and clinical data from 464 children (5–10 years old) from the Childhood Adenotonsillectomy Trial (CHAT) database. Baseline information was used to auto- matically define pediatric OSA phenotypes using a new unsupervised subject-based association network. Follow- up data (7 months later) were used to evaluate the effects of the therapeutic intervention in terms of changes in the obstructive apnea-hypopnea index (OAHI) and the resolution of OSA (OAHI < 1 event per hour). An explainable artificial intelligence (XAI) approach was also developed to assess phenotypic information as OSA resolution predictor at baseline. Results: Our approach identified three OSA phenotypes (PHOSA1-PHOSA3), with PHOSA2 showing significantly lower odds of OSA recovery than PHOSA1 and PHOSA3 when treatment information was not considered (odds ratios, OR: 1.64 and 1.66, 95 % confidence intervals, CI: 1.03–2.62 and 1.01–2.69, respectively). The odds of OSA recovery were also significantly lower in PHOSA2 than in PHOSA3 when adenotonsillectomy was adopted as treatment (OR: 2.60, 95 % CI: 1.26–5.39). Our XAI approach identified 79.4 % (CI: 69.9–88.0 %) of children reaching OSA resolution after adenotonsillectomy, with a positive predictive value of 77.8 % (CI: 70.3 %-86.0 %). Conclusions: Our new subject-based association network successfully identified three clinically useful pediatric OSA phenotypes with different odds of therapeutic intervention effectiveness. Specifically, we found that chil- dren of any sex, >6 years old, overweight or obese, and with enlarged neck and waist circumference (PHOSA2) have less odds of recovering from OSA. Similarly, younger female children with no enlarged neck (PHOSA3) have higher odds of benefiting from adenotonsillectomy.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationAssociation networkes
dc.subject.classificationChildhood adenotonsillectomy triales
dc.subject.classificationObstructive sleep apneaes
dc.subject.classificationPhenotypeses
dc.subject.classificationExplainable artificial intelligencees
dc.titleA subject-based association network defines new pediatric sleep apnea phenotypes with different odds of recovery after treatmentes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2025 The Author(s)es
dc.identifier.doi10.1016/j.cmpb.2025.109209es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0169260725006248es
dc.identifier.publicationfirstpage109209es
dc.identifier.publicationtitleComputer Methods and Programs in Biomedicinees
dc.identifier.publicationvolume275es
dc.peerreviewedSIes
dc.description.projectUnión Europea a través del Programa Interreg VI-A España-Portugal (POCTEP) 2021-2027 (0043_NET4SLEEP_2_E)es
dc.description.projectEsta investigación ha sido cofinanciada por las subvenciones del Ministerio de Ciencia e Innovación - MCIN/AEI/10.13039/501100011033/, FEDER A way of making Europe y NextGenerationEU/PRTR, y por el CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN) a través del Instituto de Salud Carlos III, cofinanciado con fondos FEDER, así como por el proyecto TinyHeart de la convocatoria Early Stage de 2022 y SleepyHeart de la convocatoria Valorization de 2020 ((grants PID2020–115468RB-I00 and PDC2021–120775-I00)es
dc.description.projectEl Ensayo de Adenoamigdalectomía Infantil (CHAT) recibió el apoyo de los Institutos Nacionales de Salud (HL083075, HL083129, UL1-RR-024134, UL1 RR024989)es
dc.description.projectEl Recurso Nacional de Investigación del Sueño recibió el apoyo del Instituto Nacional del Corazón, los Pulmones y la Sangre (R24 HL114473, 75N92019R002)es
dc.description.projectMinisterio de Ciencia e Innovación - Agencia Estatal de Investigación, cofinanciada por el Fondo Social Europeo (beca "Ramón y Cajal" (RYC2019–028566-I))es
dc.description.projectInstitutos Nacionales de Salud (NIH) (becas HL16617 y AG061824)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco32 Ciencias Médicases


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