Clinical trial Recruiting at 1 site Observational Ages 18 and up

Predicting blood clots after lung cancer surgery

Official title: Prospective Cohort Study on Risk Factors and Machine Learning-Based Prediction of Postoperative Venous Thromboembolism in Patients Undergoing Lung Cancer Surgery

Run by The First Hospital of Jilin University · NCT07439991 · Data updated 2026-11-12

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 typeObservational
Ages18 Years and up
SexAll
Enrollment900 (estimated)
SponsorThe First Hospital of Jilin University
Academic / other
Locations1 site (Changchun, Jilin)
StatusRecruiting
StartedNovember 1, 2024
Main results expectedNovember 1, 2029
Study endsNovember 30, 2029
Registry record updatedFebruary 27, 2026
Trial IDNCT07439991 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a 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.

Probably 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.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

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.

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 gone: 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.

Who can join: the full rules

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 it's running

  • The First Hospital of Jilin University, Department of Thoracic Surgery
    Changchun, Jilin, China
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.