[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100620612":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":13,"centralContacts":18,"locations":28,"responsibleParty":45,"collaborators":7,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":53,"eligibilityCriteria":54,"healthyVolunteers":49,"sex":55,"minAge":56,"maxAge":57,"enrollmentInfo":58,"targetDuration":61,"studyType":62,"phases":7,"briefSummary":63,"conditions":64,"keywords":66,"overallStatus":69,"whyStopped":7,"lastUpdateSubmitDate":70,"lastUpdatePostDateStruct":71,"startDateStruct":74,"completionDateStruct":76,"leadSponsor":78,"locationsCount":79},{"fullName":5,"class":6},"University Hospital, Rouen","OTHER",null,[9],{"type":10,"name":11,"description":12,"armGroupLabels":7,"otherNames":7},"DIAGNOSTIC_TEST","Evaluation of prognostic performance of a defined score using a machine learning method (STABL: Stability Selection) integrating immune data (cytometric and proteomic)","Determination of the area under the curve (AUC) Receiver Operating Curve (ROC) for predicting complications calculated from the score obtained by the machine learning method and the occurrence of at least one major pulmonary complication among the following in the first 7 postoperative days: postoperative pneumonia, pleural effusion, postoperative atelectasis, pneumothorax, bronchospasm and acute respiratory distress syndrome.",[14],{"name":15,"affiliation":16,"role":17},"Jean JS SELIM, Doctor","Service de Anesthésie-Réanimation Médecine périopératoire CHU de Rouen","STUDY_DIRECTOR",[19,25],{"name":20,"role":21,"phone":22,"phoneExt":23,"email":24},"Nabila NL LAAJAIL, Director","CONTACT","02 32 88 82 65","+33","Nabila.Laajail@chu-rouen.fr",{"name":26,"role":21,"phone":22,"phoneExt":23,"email":27},"Vincent VF FERRANTI, ARC","Vincent.Ferranti@chu-rouen.fr",[29],{"facility":16,"status":7,"city":30,"state":7,"zip":31,"country":32,"countryCode":33,"cosmosGeoPoint":34,"geoPoint":39,"contacts":40},"Rouen","76100","France","FR",{"type":35,"coordinates":36},"Point",[37,38],1.09932,49.44313,{"lat":38,"lon":37},[41],{"name":42,"role":21,"phone":43,"phoneExt":23,"email":44},"Naomi ND DAMES, Doctor","02 32 88 68 28","Naomi.Dames@chu-rouen.fr",{"type":46,"investigatorFullName":7,"investigatorTitle":7,"investigatorAffiliation":7,"oldNameTitle":7,"oldOrganization":7},"SPONSOR","100620612","prediction-of-postoperative-pulmonary-complications-in-thoracic-surgery-100620612",false,"NCT07359885","Prediction of Postoperative Pulmonary Complications in Thoracic Surgery","Prediction of Postoperative Pulmonary Complications in Thoracic Surgery: an Immuno-inflammatory Approach","PREDICT-PPC","Inclusion Criteria:\n\n* Age ≥ 18 years\n* ASA score ≤ 3\n* Patients undergoing scheduled video-assisted or robot-assisted lobectomy, bilobectomy, or segmentectomy.\n* Patients who have read and understood the information letter and do not object to the research.\n* For women of childbearing age (non-sterile): effective contraception\n* Menopausal (non-medically induced amenorrhea for at least 12 months)\n* Patients covered by a social security scheme\n\nExclusion Criteria:\n\n* Minor patients\n* Surgery scheduled for a Friday\n* Patients undergoing a pneumonectomy\n* Pregnant or breastfeeding women\n* Patients deprived of their liberty by an administrative or judicial decision, as well as those under legal protection, guardianship, or curatorship","ALL","18 Years","99 Years",{"count":59,"type":60},100,"ESTIMATED","3 Months","OBSERVATIONAL","Lung cancer is a common disease, and its treatment is lobectomy or pulmonary segmentectomy. In France, approximately 8,000 patients undergo this procedure each year, but it remains associated with significant Postoperative Pulmonary Complications (PPC). This surgical trauma triggers a multicellular and orchestrated immune response, necessary for defense against pathogens, as well as for inflammatory resolution and wound healing. Preoperative single-cell analysis of the patient's immune system is therefore a promising strategy for identifying biomarkers of postoperative pulmonary complications (PPC). Brice Gaudilliere's laboratory at Stanford University, in collaboration with the Paris-based startup Surge, has developed and patented a multivariate model integrating mass cytometry data, proteomic analyses, and clinical data collected before surgery to accurately predict surgical site complications after major abdominal surgery. However, no study has yet explored the identification of inflammatory biomarkers predictive of PPC after thoracic surgery.",[65],"Postoperative Pulmonary Complications (PPCs)",[67,68],"lung cancer","immuno-inflammatory approach","NOT_YET_RECRUITING","2026-01-14",{"date":72,"type":73},"2026-01-22","ACTUAL",{"date":75,"type":60},"2026-06-01",{"date":77,"type":60},"2029-03-01",{"name":5,"class":6},1]