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Updated: Jul 16, 2026

A Simplified Stepwise Approach to Echo Guidance during Percutaneous Mitral Valve Repair
Published on: October 16, 2021
What does the automated performance metric "console time" tell in robotically assisted mitral valve repair?
Kei Kobayashi1, Yizhan Guo1, Andrea Amabile1
1Division of Cardiac Surgery, Department of Cardiothoracic Surgery, University of Pittsburgh and UPMC Heart and Vascular Institute, 200 Lothrop Street C-718, Pittsburgh, PA, 15213, USA.
Console time in robotically assisted mitral valve repair (raMVR) correlates with procedural complexity and operative intensity. This automated metric can predict operative intensity and aid in surgical planning and outcome assessment.
Area of Science:
- Cardiac Surgery
- Robotic Surgery
- Medical Technology
Background:
- Console time is an automated performance metric (APM) in robotic cardiac surgery.
- Its predictive value for cardiac surgery outcomes is not well understood.
Purpose of the Study:
- To evaluate factors associated with console time during robotically assisted mitral valve repair (raMVR).
- To assess the relationship between console time and pre-, intra-, and post-operative outcomes.
Main Methods:
- Analysis of data from 150 raMVR patients (7/2021-12/2024).
- Extraction of console time and APMs from robotic system logs.
- Application of correlation analysis, multivariable linear regression, and MANOVA.
Main Results:
- Mean console time was 123.2 ± 47.0 min.
- Console time correlated with BMI, cardiopulmonary bypass (CPB) time, aortic cross-clamp (ACC) time, and hospital stay.
- Factors like decalcification, ACC time, CPB time, complex repair techniques, and annular calcification independently predicted longer console times.
- Higher console time tertiles were associated with poorer postoperative outcomes, with lower tertiles showing increased likelihood of intraoperative extubation.
Conclusions:
- Console time is a valuable, objective metric reflecting procedural complexity and operative intensity in raMVR.
- It can be utilized for intra-operative assessment, surgical planning, and early prediction of outcomes in robotic cardiac surgery programs.
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