[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100633321":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":19,"locations":25,"responsibleParty":37,"collaborators":10,"id":41,"slug":42,"hasResults":43,"nctId":44,"briefTitle":45,"officialTitle":46,"acronym":10,"eligibilityCriteria":47,"healthyVolunteers":43,"sex":48,"minAge":49,"maxAge":50,"enrollmentInfo":51,"targetDuration":54,"studyType":55,"phases":10,"briefSummary":56,"conditions":57,"keywords":59,"overallStatus":63,"whyStopped":10,"lastUpdateSubmitDate":64,"lastUpdatePostDateStruct":65,"startDateStruct":68,"completionDateStruct":70,"leadSponsor":72,"locationsCount":73},{"fullName":5,"class":6},"Konya City Hospital","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Preterm Infants Cohort (\u003C32 weeks or \u003C1500 g)",null,"This cohort includes preterm infants born before 32 weeks of gestation or weighing less than 1,500 grams, followed at the Neonatal Intensive Care Unit of Konya City Hospital. Clinical data from the first, second, and third postnatal weeks are retrospectively collected for analysis. No interventions are applied; AI models are used to predict BPD risk based on existing clinical data.",[13],"Other: Artificial Intelligence-Based Risk Prediction",[15],{"type":6,"name":16,"description":17,"armGroupLabels":18,"otherNames":10},"Artificial Intelligence-Based Risk Prediction","Different large language models (ChatGPT, Gemini, Claude) will analyze retrospective clinical data to predict the risk of bronchopulmonary dysplasia (BPD). This is an observational evaluation; no experimental treatment or therapy is administered.",[9],[20],{"name":21,"role":22,"phone":23,"phoneExt":10,"email":24},"Melek Büyükeren, Assoc. Prof. Dr.","CONTACT","+90532-780-30-78","melekbuyukeren@gmail.com",[26],{"facility":27,"status":10,"city":28,"state":10,"zip":29,"country":30,"countryCode":10,"cosmosGeoPoint":31,"geoPoint":36,"contacts":10},"Konya City Hospital, İstiklal, Adana Çevre Yolu Cd. No:135\u002F1","Konya","42020","Turkey (Türkiye)",{"type":32,"coordinates":33},"Point",[34,35],32.48464,37.87135,{"lat":35,"lon":34},{"type":38,"investigatorFullName":39,"investigatorTitle":40,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Melek Buyukeren","Associate Professor, Department of Neonatology, Konya City Hospital","100633321","early-prediction-of-bronchopulmonary-dysplasia-in-preterm-infants-using-clinical-data-100633321",false,"NCT07525167","Early Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Clinical Data","Early Prediction of Bronchopulmonary Dysplasia Using Clinical Data From the First Three Postnatal Weeks in Preterm Infants: A Retrospective Study With Large Language Models","Inclusion Criteria:\n\n* Preterm infants born before 32 weeks of gestation or with birth weight \\\u003C1,500 grams\n* Admitted and followed in the Neonatal Intensive Care Unit (NICU) of Konya City Hospital\n* Availability of complete clinical data in hospital records\n* Documented bronchopulmonary dysplasia (BPD) outcome status\n\nExclusion Criteria:\n\n* Presence of major congenital anomalies\n* Incomplete or missing clinical data\n* Death shortly after birth with insufficient follow-up data to determine BPD status","ALL","0 Days","28 Days",{"count":52,"type":53},108,"ESTIMATED","3 Weeks","OBSERVATIONAL","Early Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Clinical Data from the First Three Postnatal Weeks with Large Language Models: A Retrospective Study This retrospective, observational study aims to evaluate the early prediction of bronchopulmonary dysplasia (BPD) in preterm infants using clinical data from the first, second, and third postnatal weeks. The study includes infants born before 32 weeks of gestation or weighing less than 1,500 grams, followed at the Neonatal Intensive Care Unit of Konya City Hospital.\n\nThe study will compare the performance of different large language models (LLMs), including ChatGPT, Gemini, and Claude, in predicting BPD development. Clinical variables such as gestational age, birth weight, respiratory support, oxygen requirement, mechanical ventilation duration, and infection status will be used.\n\nPrimary outcome: Accuracy of BPD risk prediction by each AI model compared to actual clinical outcomes. Secondary outcomes: Sensitivity and specificity of predictions, weekly prediction performance, and comparative performance among AI models.\n\nThe results will provide insight into the potential clinical utility of AI-based approaches for early BPD risk assessment in preterm infants.",[58],"Bronchopulmonary Dysplasia",[58,60,61,62],"Machine Learning","Artificial Intelligence","preterm infant","NOT_YET_RECRUITING","2026-04-12",{"date":66,"type":67},"2026-04-15","ACTUAL",{"date":69,"type":53},"2026-05-01",{"date":71,"type":53},"2026-12-31",{"name":5,"class":6},1]