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

Condition(s) studied

Investigational drug(s) / intervention(s)

Prospective Perioperative Data Collection: 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.

Study 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

Primary outcome measure(s)

• Incidence of postoperative deep vein thrombosis (DVT) in lung cancer surgery patients — From the day of lung cancer surgery to 30 days postoperatively
  The primary outcome is the occurrence of postoperative deep vein thrombosis (DVT) within 30 days after lung cancer surgery, confirmed by Doppler ultrasound of the lower extremities. Perioperative clinical, laboratory, and imaging variables will be collected prospectively and analyzed to identify risk factors and develop machine learning-based predictive models for individual DVT risk.

Trial sites (1)

More The First Hospital of Jilin University trials in China

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