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Multimodal AI-Guided Recovery Management After Lung Cancer Surgery (AI-LungRecover)

G

Guangzhou Medical University

Status

Enrolling

Conditions

Randomized Controlled Trial (RCT)
Artificial Intelligence (Al)
Rehabilitation
Postoperative Care

Treatments

Behavioral: Large Language Model-Assisted Rehabilitation Nursing
Behavioral: Conventional Internet-Based Rehabilitation Information

Study type

Interventional

Funder types

Other

Identifiers

NCT07588737
ES-2025-144-01

Details and patient eligibility

About

This study is a multicenter, prospective, randomized controlled trial designed to evaluate the effectiveness and safety of a multimodal artificial intelligence (AI)-guided postoperative recovery management system in patients after lung cancer surgery. Eligible patients will be enrolled after surgery when their clinical condition is stable and will be randomly assigned to either an AI-guided recovery management group or a usual postoperative care group.

Patients in the AI-guided group will receive usual postoperative care plus a multimodal AI-based recovery management system. The system will collect patient-reported symptoms, vital signs, physical activity, respiratory rehabilitation information, recovery-related data, and, when needed, wound or chest-related images or short videos. Based on these data, the system will provide recovery feedback, general nursing advice, respiratory rehabilitation reminders, activity guidance, and risk stratification alerts. For red-flag symptoms or high-risk conditions, the system will advise patients to contact the clinical team or seek medical care.

Patients in the usual-care group will receive standard postoperative management after lung cancer surgery and will complete symptom assessments at the same prespecified time points, but they will not receive AI-generated individualized recovery feedback or AI-generated risk alerts.

The primary outcome is the number of MDASI-LC-derived target symptom threshold events within 30 days after surgery. Target symptoms include pain, fatigue, disturbed sleep, shortness of breath, and cough. Secondary outcomes include overall target symptom burden, quality of recovery, time to recovery to a mild-symptom state, functional interference, respiratory rehabilitation adherence, physical activity adherence, unplanned healthcare utilization, pulmonary complications, and unplanned readmission.

Full description

Patients recovering from lung cancer surgery commonly experience postoperative symptoms such as pain, cough, shortness of breath, fatigue, disturbed sleep, reduced physical activity, and anxiety. These symptoms may affect recovery experience, daily function, adherence to respiratory rehabilitation, and timely initiation of subsequent anticancer treatment. Conventional postoperative management usually relies on inpatient nursing care, discharge education, scheduled outpatient follow-up, and patient-initiated contact with healthcare professionals. However, symptoms can change rapidly during the early postoperative period and after discharge, and conventional follow-up may not provide continuous and individualized identification of symptom burden, recovery needs, or potential risks.

This trial will evaluate whether a multimodal AI-guided postoperative recovery management system can improve early recovery after lung cancer surgery. The AI-guided system is designed to integrate multiple types of patient-generated data, including patient-reported symptoms, vital signs, physical activity, respiratory rehabilitation completion, medication and nursing adherence, and, when needed, wound, drainage-site, or chest-related images or short videos. The system will provide postoperative recovery feedback, general nursing advice, respiratory rehabilitation reminders, activity guidance, symptom management suggestions, and risk stratification alerts.

The AI system is not intended to diagnose postoperative complications, prescribe medication, recommend self-adjustment of prescription drugs, or replace the clinical judgment of physicians or nurses. For red-flag symptoms or high-risk conditions, the system will advise patients to contact the clinical team or seek medical care. Both study groups will retain access to usual clinical safety pathways throughout the trial.

Participants will be randomly assigned in a 1:1 ratio to the AI-guided recovery management group or the usual postoperative care group. The AI-guided group will receive usual postoperative care plus the multimodal AI recovery management system from postoperative intervention initiation to postoperative day 30. The usual-care group will receive standard postoperative management, including routine inpatient care, pain management, respiratory exercise instruction, activity and diet advice, medication guidance, discharge education, outpatient follow-up arrangements, and routine telephone or online follow-up where applicable. To ensure consistent outcome measurement, participants in both groups will complete patient-reported symptom assessments at the same prespecified time points.

The primary outcome is the number of MDASI-LC-derived target symptom threshold events per patient within 30 days after surgery. Target symptoms include pain, fatigue, disturbed sleep, shortness of breath, and cough. Each target symptom will be assessed using MDASI-LC items or equivalent 0-10 numeric rating scales. A target symptom threshold event is defined as any target symptom score of 4 or higher at a prespecified assessment time point. The study will also evaluate overall target symptom burden, postoperative quality of recovery, time to recovery to a mild-symptom state, MDASI-LC functional interference, adherence to respiratory rehabilitation exercises, adherence to physical activity recommendations, unplanned healthcare utilization, pulmonary complications, unplanned readmission, and AI-related safety and feasibility outcomes.

Enrollment

868 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  1. Age 18 years or older.
  2. Clinically or pathologically diagnosed with lung cancer.
  3. Undergoing lung cancer-related thoracic surgery.
  4. Surgical procedures may include video-assisted thoracoscopic surgery, robot-assisted thoracic surgery, or open thoracic surgery.
  5. Surgical extent may include wedge resection, segmentectomy, lobectomy, sleeve resection, combined resection, bilobectomy, or pneumonectomy.
  6. Clinically stable after surgery and able to participate in symptom assessment and postoperative recovery management.
  7. Able to use a smartphone or study device, or has a caregiver who can assist with use.
  8. Able to complete patient-reported symptom assessments and postoperative recovery information reporting.
  9. Provides written informed consent.

Exclusion criteria

  1. Patients receiving non-surgical treatment only.
  2. Patients undergoing bronchoscopy, percutaneous biopsy, or other non-surgical diagnostic or therapeutic procedures only.
  3. Clinically unstable after surgery and unable to participate in symptom assessment or recovery management.
  4. Requiring prolonged intensive care unit treatment, continuous advanced life support, or continuous intensive medical management.
  5. Severe cognitive impairment, psychiatric disorder, language communication disorder, or other conditions that preclude completion of study assessments.
  6. Unable to use a smartphone or study device and without a caregiver who can assist with use.
  7. Currently participating in another interventional clinical study that may affect the primary outcome of this trial.
  8. Any other condition judged by the investigator to make the patient unsuitable for participation in this study.

Trial design

Primary purpose

Supportive Care

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

868 participants in 2 patient groups

Conventional Internet Group
Active Comparator group
Description:
Participants in this group will receive routine postoperative rehabilitation nursing and use conventional internet-based information resources for rehabilitation-related information after thoracic surgery.
Treatment:
Behavioral: Conventional Internet-Based Rehabilitation Information
Large Language Model-Assisted Rehabilitation Nursing Group
Experimental group
Description:
Participants in this group will receive artificial intelligence-assisted postoperative rehabilitation nursing through a large language model-based system. The system will analyze postoperative patient data and provide individualized rehabilitation recommendations, including pain management, pulmonary function training, and exercise rehabilitation.
Treatment:
Behavioral: Large Language Model-Assisted Rehabilitation Nursing

Trial contacts and locations

1

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Central trial contact

Jianxing He

Data sourced from clinicaltrials.gov

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