AI-Personalized Discharge Education After Lung Cancer Surgery

Is this trial a fit for you?

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

What this trial studies

This randomized, single-center trial assigns adults who had lung cancer surgery to receive either routine discharge education or routine education plus an AI-generated, personalized discharge plan. The AI guidance is created from patient-specific surgical and health data and is reviewed by a nurse before use. Primary outcome is the quality of discharge teaching at discharge, with secondary outcomes including postoperative self-efficacy and quality of life one month later. A total of 156 participants are involved, evenly split between groups, to see if tailored AI support improves recovery after surgery.

Why it matters

Who can join: the full rules

Inclusion Criteria:

1. Pathologically confirmed primary lung cancer and underwent radical lung cancer surgery by thoracoscopic or open approach, including lobectomy, pneumonectomy, or wedge resection.
2. Age 18 to 80 years.
3. Clinical stage I to III.
4. No distant organ metastasis.
5. Clinically stable after surgery, conscious, and able to perform basic listening, speaking, and reading activities, with planned discharge to home for recovery.
6. The participant or primary caregiver is able to use a smartphone and WeChat.
7. Able and willing to provide informed consent and voluntarily participate in the study.

Exclusion Criteria:

1. Recurrent lung cancer or previous treatment with targeted therapy, chemotherapy, or radiotherapy.
2. Severe aphasia, cognitive impairment (MMSE \<24), or psychiatric disorders that prevent independent completion of study questionnaires.
3. Severe cardiac, hepatic, or renal dysfunction, or another malignant tumor.
4. Severe postoperative complications requiring prolonged hospitalization, such as bronchopleural fistula or major bleeding.
5. Participation in another interventional clinical study.
6. Unable to complete the 1-month follow-up because of travel or residence outside the study area after discharge.

Where it's running

• Siping Central People's Hospital
  Siping, Jilin, China Recruiting

Study contacts

• Principal investigator: Yang Liu, PhD — Xiamen University
• Study coordinator: Weiguang Zhou, Master's
• Email: 254402969@qq.com
• Phone: +86 13624449503

Similar studies

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

• Boosting lung cancer screening for patients seen in the emergency department

  This project will test whether giving eligible emergency department patients a facilitated referral plus text reminders helps more people get lung cancer screening.

  Recruiting University of Rochester · Rochester, New York · NCT07287085

• Risk-based lung cancer screening in COPD patients using ML and clinical models

  This study tests whether a PLCOm2012 risk model plus a machine learning model can spot COPD patients at high risk for lung cancer to see if they benefit from low-dose CT screening.

  Recruiting Vejle Hospital · Vejle, Region Syddanmark · NCT07848815

• Next Generation Delivery System (NGDS) for SBRT in thorax and upper abdomen

  A study tests a new machine to deliver SBRT more quickly and comfortably for adults with thoracic or upper abdominal cancers.

  Recruiting at 2 sites Varian, a Siemens Healthineers Company · St Louis, Missouri and 1 other locations · NCT07824583

• Low-Intensity Endurance Exercise to Help Lung Cancer-Related Fatigue

  This trial tests whether light, regular endurance exercise can help reduce fatigue and improve quality of life for people with lung cancer in addition to their usual care.

  Recruiting Taipei Medical University · Taipei · NCT07806682

• Low-Intensity Endurance Exercise for Lung Cancer-Related Fatigue

  A randomized trial tests whether light, regular endurance exercise can help reduce fatigue and improve quality of life for people with lung cancer.

  Recruiting Taipei Medical University · Taipei · NCT07795580

• Comparing CT-guided Lung Biopsy vs Shape-Sensing Robotic Bronchoscopy for Small Nodules

  This trial tests whether shape-sensing robotic-assisted bronchoscopy with cone-beam CT can diagnose small lung nodules as well as the standard CT-guided lung biopsy, with a focus on safety.

  Recruiting at 3 sites Phase 4 Intuitive Surgical · Heidelberg and 2 other locations · NCT07761351

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.