{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T23:48:39Z","timestamp":1792453719937,"version":"4.5.0"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":590,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T00:00:00Z","timestamp":1709510400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000042","name":"Amgen Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000042","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004326","name":"Bayer","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004326","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001003","name":"Boehringer Ingelheim","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001003","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004336","name":"Novartis","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004336","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000042","name":"Amgen Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000042","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004326","name":"Bayer","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004326","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001003","name":"Boehringer Ingelheim","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001003","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004336","name":"Novartis","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004336","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>The use of large medical or healthcare claims databases is very useful for population-based studies on the burden of heart failure (HF). Clinical characteristics and management of HF patients differ according to categories of left ventricular ejection fraction (LVEF), but this information is often missing in such databases. We aimed to develop and validate algorithms to identify LVEF in healthcare databases where the information is lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>Algorithms were built by machine learning with a random forest approach. Algorithms were trained and reinforced using the French national claims database [Syst\u00e8me National des Donn\u00e9es de Sant\u00e9 (SNDS)] and a French HF registry. Variables were age, gender, and comorbidities, which could be identified by medico-administrative code-based proxies, Anatomical Therapeutic Chemical codes for drug delivery, International Classification of Diseases (Tenth Revision) coding for hospitalizations, and administrative codes for any other type of reimbursed care. The algorithms were validated by cross-validation and against a subset of the SNDS that includes LVEF information. The areas under the receiver operating characteristic curve were 0.84 for the algorithm identifying LVEF \u2264 40% and 0.79 for the algorithms identifying LVEF &amp;lt; 50% and \u226550%. For LVEF \u2264 40%, the reinforced algorithm identified 50% of patients in the validation dataset with a positive predictive value of 0.88 and a specificity of 0.96. The most important predictive variables were delivery of HF medication, sex, age, hospitalization, and testing for natriuretic peptides with different orders of positive or negative importance according to the LVEF category.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The algorithms identify reduced or preserved LVEF in HF patients within a nationwide healthcare claims database with high positive predictive value and low rates of false positives.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ehf2.14725","type":"journal-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T20:59:48Z","timestamp":1709585988000},"page":"1688-1697","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Development and Validation of Algorithms to Predict Left Ventricular Ejection Fraction Class from Healthcare Claims Data"],"prefix":"10.1093","volume":"11","author":[{"given":"Damien","family":"Logeart","sequence":"first","affiliation":[{"name":"Department of Cardiology, Paris Cit\u00e9 University, AP-HP H\u00f4pital Lariboisi\u00e8re, Inserm U942 , 2 rue Ambroise Par\u00e9, Paris ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maxime","family":"Doublet","sequence":"additional","affiliation":[{"name":"Clinityx , Boulogne-Billancourt ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaux","family":"Gouysse","sequence":"additional","affiliation":[{"name":"Clinityx , Boulogne-Billancourt ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thibaud","family":"Damy","sequence":"additional","affiliation":[{"name":"Department of Cardiology and French National Reference Centre for Cardiac Amyloidosis, H\u00f4pitaux Universitaires Henri-Mondor AP-HP, IMRB, Inserm, Universit\u00e9 Paris-Est Cr\u00e9teil , Cr\u00e9teil ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Isnard","sequence":"additional","affiliation":[{"name":"H\u00f4pital Piti\u00e9-Salp\u00e9tri\u00e8re, AP-HP , Paris ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fran\u00e7ois","family":"Roubille","sequence":"additional","affiliation":[{"name":"Department of Cardiology, INI-CRT PhyMedExp Inserm CNRS, CHU de Montpellier, Universit\u00e9 de Montpellier , Montpellier ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,3,4]]},"reference":[{"key":"2026012113030792100_ehf214725-bib-0001","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1093\/eurpub\/ckz168","article-title":"Benefits and challenges of Big Data in healthcare: An overview of the European initiatives","volume":"29","author":"Pastorino","year":"2019","journal-title":"Eur J Public Health"},{"key":"2026012113030792100_ehf214725-bib-0002","doi-asserted-by":"publisher","first-page":"2167","DOI":"10.1161\/CIR.0b013e3182181529","article-title":"The American Heart Association's recommendations for expanding the applications of existing and future clinical registries: A policy statement from the American Heart Association","volume":"123","author":"Bufalino","year":"2011","journal-title":"Circulation"},{"key":"2026012113030792100_ehf214725-bib-0003","doi-asserted-by":"publisher","first-page":"1421","DOI":"10.1161\/CIRCRESAHA.121.318172","article-title":"Epidemiology of heart failure: A contemporary perspective","volume":"128","author":"Roger","year":"2021","journal-title":"Circ Res"},{"key":"2026012113030792100_ehf214725-bib-0004","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab368","article-title":"2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure of the European Society of Cardiology (ESC). 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