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A three-step protocol was applied: microRNA (miRNA) screening (n\u2009=\u200920), technical validation (n\u2009=\u200960), and biological validation (n\u2009=\u2009587). The primary outcome was either death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening of heart failure, whatever occurred first. MiRNA quantification was performed in plasma samples using miRNA sequencing and RT-qPCR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Circulating miR-133a-3p levels were inversely associated with the primary study outcome. Nonetheless, miR-133a-3p did not improve a previously established clinical prognostic model in terms of discrimination or reclassification. A customized regression tree model constructed using the Classification and Regression Tree (CART) algorithm identified eight patient subphenotypes with specific risk patterns based on clinical and molecular characteristics. MiR-133a-3p entered the regression tree defining the group at the lowest risk; patients with log(NT-proBNP) \u2264\u20096\u00a0pg\/mL (miR-133a-3p levels above 1.5 arbitrary units). The overall predictive capacity of suffering the event was highly stable over the follow-up (from 0.735 to 0.767).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The combination of clinical information, circulating miRNAs, and decision tree learning allows the identification of specific risk subphenotypes in patients with HFrEF and CSA.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12967-023-04558-w","type":"journal-article","created":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T03:02:42Z","timestamp":1697770962000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Circulating miR-133a-3p defines a low-risk subphenotype in patients with heart failure and central sleep apnea: a decision tree machine learning approach"],"prefix":"10.1186","volume":"21","author":[{"given":"David","family":"de Gonzalo-Calvo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Martinez-Camblor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thalia","family":"Belmonte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ferran","family":"Barb\u00e9","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"Duarte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin R.","family":"Cowie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christiane E.","family":"Angermann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Korte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabelle","family":"Riedel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Josephine","family":"Labus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfgang","family":"Koenig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Faiez","family":"Zannad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Thum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"B\u00e4r","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,20]]},"reference":[{"key":"4558_CR1","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1016\/j.jacc.2021.05.048","volume":"78","author":"MR Cowie","year":"2021","unstructured":"Cowie MR, Linz D, Redline S, Somers VK, Simonds AK. 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CB and TT have filed patents on the use of circulating RNAs for diagnosis and prognosis of cardiovascular disease. WK reports advisory board fees from AstraZeneca, Novartis, Amgen, Pfizer, The Medicines Company, DalCor, Kowa, Corvidia, OMEICOS, Daiichi-Sankyo, Novo Nordisk, New Amsterdam Pharma, TenSixteen Bio, Esperion,\u00a0Genentech; lecture fees from Bristol-Myers Squibb, Novartis, Amgen, Berlin-Chemie, Sanofi and AstraZeneca; grants and non-financial support from Abbott, Roche Diagnostics, Beckmann, and Singulex, all outside the submitted work. FZ reports personal fees from Applied Therapeutics, Bayer, Boehringer, BMS, CVRx, Cardior, Cereno pharmaceutical, Cellprothera, CEVA, Merck, Novartis, NovoNordisk, Owkin, Pfizer, Servier, having stock options at G3Pharmaceutical and equities at Cereno pharmaceutical, Cardiorenal, Eshmoun Clinical research and being the founder of Cardiovascular Clinical Trialists. CEA reports membership in the ServeHF Steering committee, and received consulting fees and honoraria from ResMed, in context with the current work. She further reports grant support, personal fees and\/or non-financial support from Abbott, Astra-Zeneca, Boehringer Ingelheim & Eli Lilly Company, Biotronik, Novo Nordisk, Novartis, Thermo Fisher and Vifor, all outside of the submitted work. Members of the ServeHF Steering committee, received consulting fees and honoraria from ResMed, in context with current work","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"742"}}