| dc.contributor.author | Gutierrez Tobal, Gonzalo César | |
| dc.contributor.author | Gómez Pilar, Javier | |
| dc.contributor.author | Ferreira Santos, Daniela | |
| dc.contributor.author | Pereira Rodrigues, Pedro | |
| dc.contributor.author | Álvarez González, Daniel | |
| dc.contributor.author | Campo Matias, Félix del | |
| dc.contributor.author | Gozal, David | |
| dc.contributor.author | Hornero Sánchez, Roberto | |
| dc.date.accessioned | 2025-12-23T11:13:12Z | |
| dc.date.available | 2025-12-23T11:13:12Z | |
| dc.date.issued | 2026 | |
| dc.identifier.citation | Computer Methods and Programs in Biomedicine, 2026, vol. 275, p. 109209 | es |
| dc.identifier.issn | 0169-2607 | es |
| dc.identifier.uri | https://uvadoc.uva.es/handle/10324/81016 | |
| dc.description | Producción Científica | es |
| dc.description.abstract | Background 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.mimetype | application/pdf | es |
| dc.language.iso | eng | es |
| dc.publisher | Elsevier | es |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject.classification | Association network | es |
| dc.subject.classification | Childhood adenotonsillectomy trial | es |
| dc.subject.classification | Obstructive sleep apnea | es |
| dc.subject.classification | Phenotypes | es |
| dc.subject.classification | Explainable artificial intelligence | es |
| dc.title | A subject-based association network defines new pediatric sleep apnea phenotypes with different odds of recovery after treatment | es |
| dc.type | info:eu-repo/semantics/article | es |
| dc.rights.holder | © 2025 The Author(s) | es |
| dc.identifier.doi | 10.1016/j.cmpb.2025.109209 | es |
| dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0169260725006248 | es |
| dc.identifier.publicationfirstpage | 109209 | es |
| dc.identifier.publicationtitle | Computer Methods and Programs in Biomedicine | es |
| dc.identifier.publicationvolume | 275 | es |
| dc.peerreviewed | SI | es |
| dc.description.project | Unión Europea a través del Programa Interreg VI-A España-Portugal (POCTEP) 2021-2027 (0043_NET4SLEEP_2_E) | es |
| dc.description.project | Esta 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.project | El Ensayo de Adenoamigdalectomía Infantil (CHAT) recibió el apoyo de los Institutos Nacionales de Salud (HL083075, HL083129, UL1-RR-024134, UL1 RR024989) | es |
| dc.description.project | El 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.project | Ministerio de Ciencia e Innovación - Agencia Estatal de Investigación, cofinanciada por el Fondo Social Europeo (beca "Ramón y Cajal" (RYC2019–028566-I)) | es |
| dc.description.project | Institutos Nacionales de Salud (NIH) (becas HL16617 y AG061824) | es |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es |
| dc.subject.unesco | 32 Ciencias Médicas | es |