Observational Study of Risk Factors and Machine Learning Prediction of Blood Clots After Lung Cancer Surgery

What this Trial Is About

Researchers are investigating risk factors and prediction of postoperative venous thromboembolism VTE, specifically deep vein thrombosis DVT, in patients undergoing lung cancer surgery. The goal is to understand which clinical, surgical, and laboratory factors contribute to developing DVT after surgery and to evaluate if machine learning models can accurately predict individual risk. This observational study follows participants for 30 days after their lung cancer surgery. The study involves collecting perioperative clinical data, laboratory results, and imaging findings from adult patients who have lung cancer surgery. Participants are grouped based on whether they develop postoperative DVT within 30 days or not. The collected data will help identify risk factors and create predictive models using machine learning techniques. No treatment beyond standard care is provided as part of this data collection. During the study, participants clinical, laboratory, and imaging data will be recorded, and the occurrence of postoperative DVT will be monitored for 30 days after surgery. Researchers will analyze these data to identify risk factors and measure the incidence of DVT. Participants will be followed closely for at least 48 hours post-surgery and during the 30-day follow-up period. The study aims to improve understanding and prediction of VTE risk in lung cancer surgery patients.

Study of Risk Factors and Prediction of Blood Clots After Lung Cancer Surgery