Study of Risk Factors and Prediction of Blood Clots After Lung Cancer Surgery
Prospective Cohort Study on Risk Factors and Machine Learning-Based Prediction of Postoperative Venous Thromboembolism in Patients Undergoing Lung Cancer Surgery
The First Hospital of Jilin University
900 participants
Nov 1, 2024
OBSERVATIONAL
Conditions
Summary
The goal of this observational study is to learn about the risk factors and prediction of postoperative venous thromboembolism (VTE) in patients undergoing lung cancer surgery. The main question it aims to answer is: Which clinical, surgical, and laboratory factors are associated with the development of postoperative deep vein thrombosis (DVT) in lung cancer surgery patients, and can machine learning models accurately predict individual risk? Participants undergoing lung cancer surgery will be prospectively followed for 30 days after surgery. Perioperative clinical data, laboratory results, and imaging findings will be collected to identify VTE risk factors and to develop a predictive model.
Eligibility
Inclusion Criteria5
- Age ≥ 18 years
- Patients undergoing surgical resection for lung cancer
- Postoperative hospital stay ≥ 48 hours
- Availability of perioperative clinical, laboratory, and imaging data
- Willingness to provide informed consent and participate in 30-day follow-up
Exclusion Criteria7
- Pre-existing deep vein thrombosis (DVT) or pulmonary embolism (PE) before surgery
- Preoperative or ongoing anticoagulation therapy for ≥ 2 weeks
- Severe coagulation disorders or bleeding diseases
- Severe hepatic, renal, or hematologic dysfunction, or uncontrolled systemic infection
- Concurrent major organ surgery (e.g., cardiac, liver surgery)
- Pregnancy or lactation
- Incomplete postoperative follow-up data
Interventions
The intervention involves the prospective collection of perioperative clinical, laboratory, and imaging data from adult patients undergoing lung cancer surgery. No therapeutic or diagnostic procedures beyond standard care are applied. Collected data will be used to identify risk factors for postoperative deep vein thrombosis (DVT) and to develop machine learning-based predictive models.
Locations(1)
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NCT07439991