{"doi":"10.1016/j.cmpb.2025.109209","title":"A subject-based association network defines new pediatric sleep apnea phenotypes with different odds of recovery after treatment","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 automatically 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: 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: ) have higher odds of benefiting from adenotonsillectomy.","journal":"Computer Methods and Programs in Biomedicine","year":2025,"id":535835,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.936,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":703176,"name":"Javier Gómez‐Pilar","orcid":"0000-0001-7882-7890","position":1,"is_corresponding":false},{"id":1420046,"name":"Daniela Ferreira‐Santos","orcid":"0000-0002-0390-9944","position":2,"is_corresponding":false},{"id":1420047,"name":"Pedro Pereira Rodrigues","orcid":"0000-0001-7867-6682","position":3,"is_corresponding":false},{"id":393533,"name":"Daniel Álvarez","orcid":"0000-0003-1027-2395","position":4,"is_corresponding":false},{"id":646260,"name":"Félix del Campo","orcid":"0000-0002-4554-2167","position":5,"is_corresponding":false},{"id":278385,"name":"David Gozal","orcid":"0000-0001-8195-6036","position":6,"is_corresponding":false},{"id":81013,"name":"Roberto Hornero","orcid":"0000-0001-9915-2570","position":7,"is_corresponding":false},{"id":393531,"name":"Gonzalo C. Gutiérrez‐Tobal","orcid":"0000-0002-1237-3424","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T02:52:00.885532Z","pmid":"41411777","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}