Prediction of Postoperative Pulmonary Complications in Thoracic Surgery

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-99
SponsorUniversity Hospital, Rouen

About this trial

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.

Eligibility criteria

Qualifiers

Age ≥ 18 years

ASA score ≤ 3

Patients undergoing scheduled video-assisted or robot-assisted lobectomy, bilobectomy, or segmentectomy.

Patients who have read and understood the information letter and do not object to the research.

Disqualifiers

Minor patients

Surgery scheduled for a Friday

Patients undergoing a pneumonectomy

Pregnant or breastfeeding women

Trial design

Treatments tested in this trial

  • Evaluation of prognostic performance of a defined score using a machine learning method (STABL: Stability Selection) integrating immune data (cytometric and proteomic)

Treatment groups

No treatment groups listed

Sponsors and collaborators