AI-Generated Video Feedback to Improve Technical Skills in Coronary Artery Bypass Grafting

February 3, 2026 updated by: Shengshou Hu, China National Center for Cardiovascular Diseases
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 assessed by both an AI model and blinded human expert raters using standardized scoring criteria. Based on the AI assessment, surgeons will receive personalized video feedback highlighting operative steps associated with lower technical performance. After a one-month self-directed review period, a follow-up CABG surgical video will be submitted and evaluated using the same process. Changes in human-rated technical skill scores between baseline and follow-up will be used to assess the potential educational impact of AI-generated video feedback.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

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 surgical education.

This study aims to evaluate whether targeted video feedback generated by an AI-based surgical performance assessment model can help cardiac surgeons improve their technical skills in CABG procedures. Participating surgeons whose baseline technical performance ranked in the lower half of the AI scoring system will receive personalized video feedback highlighting operative steps and maneuvers associated with lower performance scores.

In this single-group, self-controlled study, each participating surgeon will submit a baseline CABG surgical video, which will be independently evaluated by both the AI model and a panel of experienced cardiac surgeons using standardized scoring criteria. After receiving AI-generated video feedback, surgeons will be given one month to review and reflect on the feedback without additional formal training or coaching. A follow-up CABG surgical video will then be submitted and assessed using the same evaluation process.

The primary outcome of the study is the change in technical skill scores assigned by human expert raters between the baseline and follow-up videos. Secondary outcomes include surgeons' self-assessments of AI-identified performance deficits, agreement between AI-generated feedback and human expert feedback, and selected patient postoperative in-hospital outcomes. The findings of this study may inform the role of AI-assisted video feedback as a scalable educational tool for surgical skill development.

Study Type

Interventional

Enrollment (Estimated)

100

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Beijing Municipality
      • Beijing, Beijing Municipality, China, 102300
        • Fuwai Hospital
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Baseline AI-assessed technical performance ranked in the lower 50% within the scoring system in CAMERA study (NCT06739005)

Exclusion Criteria:

  • Unwilling to attend

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: 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 reflection. No additional formal training or coaching is given during the one-month intervention period, after which a follow-up surgical video is submitted for re-evaluation.
Behavioral: 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 reflection. No additional formal training or coaching is given during the one-month intervention period, after which a follow-up surgical video is submitted for re-evaluation.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in Human Expert-Rated Technical Skill Score Between Baseline and Follow-Up CABG Videos
Time Frame: Baseline, 1 month
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

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Surgeon self-assessments of the AI feedback
Time Frame: 1 month
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.
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
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
Time Frame: Baseline, 1 month
The associations with changes in surgeon technical performance following the AI feedback intervention and the incidence of tracheotomy.
Baseline, 1 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

China National Center for Cardiovascular Diseases

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

January 31, 2026

Primary Completion (Estimated)

March 31, 2026

Study Completion (Estimated)

April 30, 2026

Study Registration Dates

First Submitted

December 23, 2025

First Submitted That Met QC Criteria

February 3, 2026

First Posted (Actual)

February 10, 2026

Study Record Updates

Last Update Posted (Actual)

February 10, 2026

Last Update Submitted That Met QC Criteria

February 3, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • FW-HSS

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Data collected for the study will be made available publicly upon reasonable request (huss@fuwai.com) after two years of publication.

IPD Sharing Time Frame

After two years of publication.

IPD Sharing Access Criteria

Anyone with a protocol sended to huss@fuwai.com and aprroved by PI can access the data. The data will be tranferred by excel or sas.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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