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Clinical Trial NCT07400172 for Cardiac, Surgery (Cardiac), Education, Artificial Intelligence (AI) is not yet recruiting. See the Trial Radar Card View and AI discovery tools for all the details. Or ask anything here. | ||
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AI-Generated Video Feedback to Improve Technical Skills in Coronary Artery Bypass Grafting 100 Personalized Treatment
Clinical Trial NCT07400172 is an interventional study for Cardiac, Surgery (Cardiac), Education, Artificial Intelligence (AI) and is currently not yet recruiting. Enrollment is planned to begin on 31 January 2026 and continue until the study accrues 100 participants. Led by China National Center for Cardiovascular Diseases, this study is expected to complete by 30 April 2026. The latest data from ClinicalTrials.gov was last updated on 10 February 2026.
Brief Summary
This study aims to evaluate whether targeted video feedback generated by an artificial intelligence (AI)-based surgical performance assessment model can support improvement in technical skills among cardiac surgeons performing coronary artery bypass grafting (CABG). This is a single-group, self-controlled, pre-post interventional study. Participating surgeons will submit a baseline CABG surgical video, which will be ...Show More
Detailed Description
Coronary artery bypass grafting (CABG) is a complex surgical procedure that requires a high level of technical skill from cardiac surgeons. Variability in surgical technique may influence procedural quality and patient outcomes. Recent advances in artificial intelligence (AI) have enabled automated assessment of surgical performance using operative video data, creating new opportunities for objective feedback and sur...Show More
Official Title
AI-Generated Video Feedback to Improve Technical Skills in Coronary Artery Bypass Grafting
Conditions
CardiacSurgery (Cardiac)EducationArtificial Intelligence (AI)Other Study IDs
- FW-HSS
NCT ID Number
Start Date (Actual)
2026-01-31
Last Update Posted
2026-02-10
Completion Date (Estimated)
2026-04-30
Enrollment (Estimated)
100
Study Type
Interventional
PHASE
N/A
Status
Not yet recruiting
Keywords
Coronary Artery Bypass Grafting
Surgical Education
Video-Based Feedback
Artificial Intelligence
Surgical Education
Video-Based Feedback
Artificial Intelligence
Primary Purpose
Other
Design Allocation
N/A
Interventional Model
Single Group
Masking
None (Open Label)
Arms / Interventions
| Participant Group/Arm | Intervention/Treatment |
|---|---|
ExperimentalAI-Guided Video Feedback Intervention Participants in this study will receive a personalized educational intervention consisting of AI-generated video feedback based on their baseline coronary artery bypass grafting (CABG) surgical videos. The AI model analyzes surgical performance and identifies specific operative steps with lower technical skill scores. Curated video clips highlighting these areas are provided to the surgeons for self-review and reflec...Show More | AI-Guided Video Feedback Intervention Participants in this study will receive a personalized educational intervention consisting of AI-generated video feedback based on their baseline coronary artery bypass grafting (CABG) surgical videos. The AI model analyzes surgical performance and identifies specific operative steps with lower technical skill scores. Curated video clips highlighting these areas are provided to the surgeons for self-review and reflec...Show More |
Primary Outcome Measures
Secondary Outcome Measures
| Outcome Measure | Measure Description | Time Frame |
|---|---|---|
Change in Human Expert-Rated Technical Skill Score Between Baseline and Follow-Up CABG Videos | The primary outcome is the change in technical skill scores assigned by a panel of blinded human expert raters, who independently evaluate anonymized coronary artery bypass grafting (CABG) surgical videos submitted at baseline and one month after receiving AI-generated video feedback. The scoring uses a standardized rubric to assess overall surgical technical performance. The higher score, the better performance: respect for tissue, time and motion, instrument handling, knowledge of instruments, use of assistants, flow of operation and forward planning, and knowledge of the specific procedure. Each domain was scored on a 5-point Likert scale, where 1 indicated poor performance and 5 represented excellence. In addition, each rater provided an overall impression score (1-5) to capture their holistic assessment of surgical performance. The two scores were scaled to 100 points and the final score consists of 70% of 7-domain rating sum scores and 30% of overall impression score. | Baseline, 1 month |
| Outcome Measure | Measure Description | Time Frame |
|---|---|---|
Surgeon self-assessments of the AI feedback | Surgeons will review the AI-generated video clips highlighting technical performance deficits and complete a self-assessment questionnaire evaluating their satisfaction of the AI feedback. | 1 month |
Consistency between AI feedback and human expert feedback. | This outcome assesses the consistency between the AI-generated surgical performance feedback and evaluations provided by human expert raters. AI-score was generated by a two-stage deep learning framework and human expert raters' score was generated by a validated 7-domain rating scale as detailed in the primary outcome. The intraclass correlation coefficient (ICC) will be used to assess the consistency between the surgical technique scores assessed by the AI model and those rated by human expert raters. | Baseline, 1 month |
Postoperative in-hospital outcomes: the icidence of major complications | Patient postoperative in-hospital outcomes will be collected and analyzed to explore any associations with changes in surgeon technical performance following the AI feedback intervention. The incidence of major complications (a composite outcome of death, acute kidney injury, myocardial infarction and stroke) | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of death | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of death. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of acute kidney injury | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of acute kidney injury. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of myocardial infarction | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of myocardial infarction. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of stroke | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of stroke. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of secondary thoracotomy | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of secondary thoracotomy. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of IABP implantation | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of IABP implantation. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of ECMO implantation | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of ECMO implantation. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of bedside hemofiltration | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of bedside hemofiltration. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of peritoneal dialysis | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of peritoneal dialysis. | Baseline, 1 month |
Postoperative in-hospital outcomes: the incidence of tracheotomy | The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of tracheotomy. | Baseline, 1 month |
Participation Assistant
Eligibility Criteria
Eligible Ages
Child, Adult, Older Adult
Eligible Sexes
All
Accepts Healthy Volunteers
Yes
- Baseline AI-assessed technical performance ranked in the lower 50% within the scoring system in CAMERA study (NCT06739005)
- Unwilling to attend
China National Center for Cardiovascular DiseasesStudy Responsible Party
Shengshou Hu, Principal Investigator, Prof, China National Center for Cardiovascular Diseases
Study Central Contact
Contact: Lihua Zhang Zhang, M.D, Ph.D, 13810483387, [email protected]
1 Study Locations in 1 Countries
Beijing Municipality
Fuwai Hospital, Beijing, Beijing Municipality, 102300, China
Lihua Zhang Zhang, M.D, Ph.D, Contact, 15920826832, [email protected]