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NCT Number: NCT06739005

AI Model for Assessing Cardiac Surgeons' Techniques

The goal of this study aims to investigate the use of artificial intelligence to analyze and evaluate the characteristics and proficiency of surgeons during vascular anastomosis in coronary artery bypass grafting (CABG) procedures. The main question it aims to answer is:

Consistency assessment between AI evaluation scores and human expert evaluation scores for surgeons during left anterior descending (LAD) artery anastomosis.

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Key information

Conditions

CABG-patients Artificial Intelligence (AI) CABG Cardiovascular Surgery Surgeons

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Fuwai Hospital, CAMS & PUMC

Beijing, Beijing Municipality, 100037, China

Location status: Recruiting

Location contact

Xin Yuan, MD, PhD

CONTACT

[email protected]

8601060866517

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age ≥ 18 years
  • Undergoing internal mammary artery-to-left anterior descending artery bypass grafting
  • First-time recipient of isolated CABG surgery
  • Signed written informed consent

Exclusion criteria

  • Patients with acute coronary syndrome
  • Patients with contraindications to coronary CT angiography or coronary angiography
  • Patients with renal insufficiency or active liver disease, including those with persistently elevated serum transaminases of unknown cause or any serum transaminase levels exceeding three times the upper limit of normal.

Treatment and study plan

Primary outcomes

  1. Consistency assessment between AI surgical evaluation scores and human expert scores.

    Time frame: At the end of enrollment

Secondary outcomes

  1. Intraoperative measurement of graft flow and flow resistance.

    Time frame: After enrollment

  2. Characteristics of the surgeon's motion trajectory.

    Time frame: After enrollment

  3. Consistency assessment between AI surgical evaluation scores levels and human expert scores levels.

    Time frame: After enrollment

    AI surgical evaluation scores levels were divided into the following 3 score levels: low, middle, high; human expert scores levels were divided into the following 3 score levels: low, middle, high.

Other outcomes

  1. Graft patency at 1 year postoperatively.

    Time frame: At 1 year

  2. Adverse cardiovascular events, such as myocardial infarction and stroke, within 6 months postoperatively.

    Time frame: At 6 months

  3. Adverse cardiovascular events, such as myocardial infarction and stroke, within 12 months postoperatively.

    Time frame: At 12 months

  4. Surgeon-level subgroup: age

    Time frame: Baseline

    Age subgroup is stratified into: <45, ≥45 years old

  5. Surgeon-level subgroup: sex

    Time frame: Baseline

    Sex subgroup is stratified into: female, male

  6. Surgeon-level subgroup: professional title

    Time frame: Baseline

    Professional title subgroup is stratified into: junior, associate, senior

  7. Surgeon-level subgroup: annual surgery volume

    Time frame: Baseline

    Annual surgery volume subgroup is stratified by tertiles

  8. Surgeon-level subgroup: total surgery volume

    Time frame: Baseline

    Total surgery volume subgroup is stratified by tertiles

  9. Surgeon-level subgroup: annual CABG volume

    Time frame: Baseline

    Annual CABG volume subgroup is stratified by tertiles

  10. Surgeon-level subgroup: total CABG volume

    Time frame: Baseline

    Total CABG volume subgroup is stratified by tertiles

  11. Patient-level subgroup: age

    Time frame: Baseline

    Age subgroup is stratified into: <65, ≥65 years old

  12. Patient-level subgroup: sex

    Time frame: Baseline

    Sex subgroup is stratified into: female, male

  13. Patient-level subgroup: the severity of coronary artery disease

    Time frame: Baseline

    The severity of coronary artery disease is measured by SYNTAX score and is stratified into: <23, 23-32, >32

Study contacts

Contact information is provided by the study sponsor or research team.

Lihua Zhang, M.D, Ph.D

CONTACT

[email protected]

8613641359895

Sponsors and collaborators

Lead sponsor

China National Center for Cardiovascular Diseases

Other Gov

Registry information

Official study title

artifiCiAl Intelligence Model for Evaluating the Surgical Techniques of caRdiAc Surgeons (CAMERA)

Acronym: CAMERA

Important dates

Study start
2025
Primary completion
2026
Study completion
2027
First posted
Dec 18, 2024
Registry last updated
Sep 23, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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