[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100581023":3},{"organization":4,"armGroups":7,"interventions":17,"overallOfficials":10,"centralContacts":10,"locations":22,"responsibleParty":41,"collaborators":10,"id":45,"slug":46,"hasResults":47,"nctId":48,"briefTitle":49,"officialTitle":50,"acronym":10,"eligibilityCriteria":51,"healthyVolunteers":47,"sex":52,"minAge":53,"maxAge":10,"enrollmentInfo":54,"targetDuration":57,"studyType":58,"phases":10,"briefSummary":59,"conditions":60,"keywords":10,"overallStatus":25,"whyStopped":10,"lastUpdateSubmitDate":62,"lastUpdatePostDateStruct":63,"startDateStruct":66,"completionDateStruct":68,"leadSponsor":70,"locationsCount":71},{"fullName":5,"class":6},"Kanuni Sultan Suleyman Training and Research Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-Generated PEEP Group (Experimental Group)",null,"Patients in this group will have their optimal PEEP levels determined using AI models (ChatGPT, DeepSeek, and Gemini). AI models will analyze mechanical ventilation data, including compliance, elastance, auto-PEEP, time constant, and pressure-volume (P-V) curves, to generate PEEP recommendations. These AI-generated values will be recorded and analyzed for accuracy, clinical relevance, and agreement with expert decisions.",[13],"Other: AI-Assisted PEEP Optimization",{"label":15,"type":10,"description":16,"interventionNames":10},"Expert-Determined PEEP Group (Control Group)","In this group, PEEP titration will be performed manually by ICU specialists using standard clinical protocols. Experts will determine PEEP levels based on lower and upper inflection point identification and pressure-volume curve analysis. Their decisions will serve as the reference standard for evaluating the AI-generated recommendations.",[18],{"type":6,"name":19,"description":20,"armGroupLabels":21,"otherNames":10},"AI-Assisted PEEP Optimization","In this study, three artificial intelligence (AI) models (ChatGPT, DeepSeek, and Gemini) will analyze mechanical ventilation data, including compliance, elastance, auto-PEEP, time constant, and pressure-volume (P-V) curves, to generate patient-specific PEEP recommendations.\n\nThese AI-generated recommendations will be compared with manual PEEP titration performed by experienced ICU specialists. The AI models will also provide abnormal ventilation parameter detection, diagnostic suggestions, and treatment recommendations. The study aims to evaluate the reliability, accuracy, and clinical applicability of AI-generated outputs in optimizing PEEP settings for mechanically ventilated ICU patients.",[9],[23],{"facility":24,"status":25,"city":26,"state":10,"zip":27,"country":28,"countryCode":10,"cosmosGeoPoint":29,"geoPoint":34,"contacts":35},"Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital","RECRUITING","Istanbul","34303","Turkey (Türkiye)",{"type":30,"coordinates":31},"Point",[32,33],28.94966,41.01384,{"lat":33,"lon":32},[36],{"name":37,"role":38,"phone":39,"phoneExt":10,"email":40},"Engin ihsan Turan","CONTACT","05382431114","enginihsan@hotmail.com",{"type":42,"investigatorFullName":43,"investigatorTitle":44,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Engin Ihsan Turan","anesthesiology and reanimation specialist","100581023","evaluation-of-ai-models-in-determining-the-optimal-peep-100581023",false,"NCT06844916","Evaluation of AI Models in Determining the Optimal PEEP","Evaluation of the Success of Artificial Intelligence Models in Determining the Optimal Positive End-Expiratory Pressure (PEEP) in Mechanical Ventilation in Intensive Care","Inclusion Criteria:\n\n* Patients aged 18 years or older (adult patient group).\n* Patients requiring mechanical ventilation in the intensive care unit (ICU).\n* Hemodynamically stable patients with stable blood pressure and heart rate.\n* Patients with complete medical records, including arterial blood gas values and ventilation parameters.\n* Patients whose legal representatives (if applicable) have provided informed consent for study participation.\n\nExclusion Criteria:\n\n* Patients receiving extracorporeal membrane oxygenation (ECMO).\n* Patients with severe hemodynamic instability, such as refractory hypotension or arrhythmias requiring continuous vasopressor support.\n* Patients with incomplete medical records, particularly those missing critical data on ventilation parameters or arterial blood gas analysis.\n* Patients or their legal representatives who decline participation in the study.","ALL","18 Years",{"count":55,"type":56},145,"ESTIMATED","7 Days","OBSERVATIONAL","his study is designed as a prospective observational clinical trial. Patients over 18 years old who are hemodynamically stable and require mechanical ventilation in the Intensive Care Unit (ICU) will be included. The inclusion criteria ensure that participants require individualized ventilatory optimization.\n\nThe study will involve a comparison between Artificial Intelligence (AI)-generated Positive End-Expiratory Pressure (PEEP) recommendations and expert-determined PEEP levels. ICU specialists will perform PEEP titration manually based on standardized protocols, identifying the lower inflection point (LIP) and upper inflection point (UIP) to optimize ventilation. The pressure-volume (P-V) curve will be analyzed to ensure optimal alveolar recruitment and prevent overdistension.\n\nStudy Procedures\n\nParticipants will:\n\nUndergo systematic mechanical ventilation assessments, including inspiratory hold and expiratory hold maneuvers, compliance, elastance, auto-PEEP, and time constant evaluations.\n\nHave ventilation data collected and analyzed using three AI models: ChatGPT, DeepSeek, and Gemini.\n\nReceive AI-generated recommendations regarding optimal PEEP levels, abnormal ventilation parameters, and potential treatment suggestions.\n\nHave their AI-based PEEP recommendations compared with those determined by ICU specialists with at least five years of experience.\n\nOutcome Measures\n\nThe study will compare AI and expert assessments based on the following primary and secondary measures:\n\nPrimary Outcome: Agreement between AI-generated PEEP levels and expert-determined PEEP levels.\n\nSecondary Outcomes:\n\nAI sensitivity and specificity in detecting abnormal ventilation parameters. Accuracy of AI-generated diagnoses. Clinical applicability of AI-recommended treatment strategies. This study aims to determine whether AI models can serve as reliable clinical decision support tools for ventilator management in ICU patients.",[61],"PEEP, Occult","2025-05-30",{"date":64,"type":65},"2025-06-04","ACTUAL",{"date":67,"type":65},"2025-03-01",{"date":69,"type":56},"2026-02-02",{"name":5,"class":6},1]