{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T15:39:53Z","timestamp":1785857993111,"version":"3.56.0"},"reference-count":34,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["K01 AA027811"],"award-info":[{"award-number":["K01 AA027811"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["U01AA014835"],"award-info":[{"award-number":["U01AA014835"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alcohol: Clinical and Experimental Research"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Early life factors, including parental sociodemographic characteristics, pregnancy exposures, and physical and neurodevelopmental features measured in infancy are associated with fetal alcohol spectrum disorders (FASD). The objective of this study was to evaluate the performance of a classifier model for diagnosing FASD in preschool\u2010aged children from pregnancy and infancy\u2010related characteristics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We analyzed a prospective pregnancy cohort in Western Ukraine enrolled between 2008 and 2014. Maternal and paternal sociodemographic factors, maternal prenatal alcohol use and smoking behaviors, reproductive characteristics, birth outcomes, infant alcohol\u2010related dysmorphic and physical features, and infant neurodevelopmental outcomes were used to predict FASD. Data were split into separate training (80%: <jats:italic>n<\/jats:italic>\u2009=\u2009245) and test (20%: <jats:italic>n<\/jats:italic>\u2009=\u200958; 11 FASD, 47 no FASD) datasets. Training data were balanced using data augmentation through a synthetic minority oversampling technique. Four classifier models (random forest, extreme gradient boosting [XGBoost], logistic regression [full model] and backward stepwise logistic regression) were evaluated for accuracy, sensitivity, and specificity in the hold\u2010out sample.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of 306 children evaluated for FASD, 61 had a diagnosis. Random forest models had the highest sensitivity (0.54), with accuracy of 0.86 (95% CI: 0.74, 0.94) in hold\u2010out data. Boosted gradient models performed similarly, however, sensitivity was less than 50%. The full logistic regression model performed poorly (sensitivity\u2009=\u20090.18 and accuracy\u2009=\u20090.65), while stepwise logistic regression performed similarly to the boosted gradient model but with lower specificity. In a hold\u2010out sample, the best performing algorithm correctly classified six of 11 children with FASD, and 44 of 47 children without FASD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>As early identification and treatment optimize outcomes of children with FASD, classifier models from early life characteristics show promise in predicting FASD. Models may be improved through the inclusion of physiologic markers of prenatal alcohol exposure and should be tested in different samples.<\/jats:p><\/jats:sec>","DOI":"10.1111\/acer.15233","type":"journal-article","created":{"date-parts":[[2023,11,21]],"date-time":"2023-11-21T12:53:01Z","timestamp":1700571181000},"page":"122-131","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Predicting fetal alcohol spectrum disorders in preschool\u2010aged children from early life factors"],"prefix":"10.1111","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2167-8921","authenticated-orcid":false,"given":"Gretchen","family":"Bandoli","sequence":"first","affiliation":[{"name":"Department of Pediatrics University of California San Diego  San Diego California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3399-6644","authenticated-orcid":false,"given":"Claire","family":"Coles","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Emory University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5008-0887","authenticated-orcid":false,"given":"Julie","family":"Kable","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Emory University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenneth Lyons","family":"Jones","sequence":"additional","affiliation":[{"name":"Department of Pediatrics University of California San Diego  San Diego California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5864-5985","authenticated-orcid":false,"given":"Wladimir","family":"Wertelecki","sequence":"additional","affiliation":[{"name":"Department of Pediatrics University of California San Diego  San Diego California USA"},{"name":"OMNI\u2010Net Ukraine Birth Defects Program  Rivne Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lyubov","family":"Yevtushok","sequence":"additional","affiliation":[{"name":"OMNI\u2010Net Ukraine Birth Defects Program  Rivne Ukraine"},{"name":"Rivne Regional Medical Diagnostic Center  Rivne Ukraine"},{"name":"Lviv National Medical University  Lviv Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natalya","family":"Zymak\u2010Zakutnya","sequence":"additional","affiliation":[{"name":"OMNI\u2010Net Ukraine Birth Defects Program  Rivne Ukraine"},{"name":"Khmelnytsky Perinatal Center  Khmelnytsky 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