Predicting 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
This project will try to use clinical, surgical, and lab data to predict which adults having lung cancer surgery may develop blood clots after the operation.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 900 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | The First Hospital of Jilin University Academic / other |
| Locations | 1 site (Changchun, Jilin) |
| Trial ID | NCT07439991 on ClinicalTrials.gov |
What this trial studies
This observational study will follow adults undergoing surgical resection for lung cancer for 30 days after surgery to record perioperative clinical, laboratory, and imaging data. Investigators will identify clinical and surgical risk factors associated with postoperative deep vein thrombosis (DVT) and venous thromboembolism (VTE). Collected data will be used to train and test machine learning models to predict individual patient risk of postoperative VTE. Patients with pre-existing DVT/PE, prolonged anticoagulation, major concurrent surgeries, or severe organ dysfunction will be excluded and no investigational treatments are administered.
Who should consider this trial
Good fit: Adults (age ≥18) who are having surgical resection for lung cancer, will remain hospitalized at least 48 hours after surgery, and can provide informed consent and 30-day follow-up data.
Not a fit: Patients with preoperative DVT or PE, those on prolonged anticoagulation, with severe coagulation or organ dysfunction, or who cannot complete follow-up are unlikely to benefit from this observational prediction project.
Why it matters
Potential benefit: If successful, a predictive model could help doctors identify high-risk patients and target preventive measures to reduce postoperative blood clots.
How similar studies have performed: Previous studies have identified traditional risk factors and risk scores for postoperative VTE, but applying machine learning specifically to predict individual risk after lung cancer surgery is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Age ≥ 18 years 2. Patients undergoing surgical resection for lung cancer 3. Postoperative hospital stay ≥ 48 hours 4. Availability of perioperative clinical, laboratory, and imaging data 5. Willingness to provide informed consent and participate in 30-day follow-up Exclusion Criteria: 1. Pre-existing deep vein thrombosis (DVT) or pulmonary embolism (PE) before surgery 2. Preoperative or ongoing anticoagulation therapy for ≥ 2 weeks 3. Severe coagulation disorders or bleeding diseases 4. Severe hepatic, renal, or hematologic dysfunction, or uncontrolled systemic infection 5. Concurrent major organ surgery (e.g., cardiac, liver surgery) 6. Pregnancy or lactation 7. Incomplete postoperative follow-up data
Where this trial is running
Changchun, Jilin
- The First Hospital of Jilin University, Department of Thoracic Surgery — Changchun, Jilin, China (Recruiting)
Study contacts
- Study coordinator: Wei Liu
- Email: l_w01@jlu.edu.cn
- Phone: 86-13596083366
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.