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Coronary Artery Bypass

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Transit Time Flow Measurement in Robotic Totally Endoscopic Coronary Artery Bypass: What Do the Numbers Mean?

Innovations (Philadelphia, Pa.)
OBJECTIVE: Transit time flow measurement (TTFM) is valuable for assessing intraoperative graft patency in coronary artery bypass surgery (CAB). The significance of competitive native coronary flow on patency, as predicted by percentage of backflow (%...

Electrocardiography-Based Artificial Intelligence Algorithm Aids in Prediction of Long-term Mortality After Cardiac Surgery.

Mayo Clinic proceedings
OBJECTIVE: To assess whether an electrocardiography-based artificial intelligence (AI) algorithm developed to detect severe ventricular dysfunction (left ventricular ejection fraction [LVEF] of 35% or below) independently predicts long-term mortality...

Outcomes of robotic coronary artery bypass versus nonrobotic coronary artery bypass.

Journal of cardiac surgery
BACKGROUND: Robotic coronary artery bypass graft (CABG) has developed in recent decades, however, prior studies showed conflicting result of robotic CABG compared to nonrobotic CABG in terms of mortality, morbidity, and cost. Herein, we sought to ana...

Commentary: When will the robots come marching in?

Journal of cardiac surgery
Minimally invasive techniques for coronary artery bypass grafting (CABG), specifically robotic-assisted CABG has increased in popularity despite conflicting evidence. Here, we review a report by Yokoyama and colleagues to the Journal of Cardiac Surge...

The Use of Artificial Neural Networks to Determine In-Hospital Mortality After Coronary Artery Bypass Surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: The aim of this study was to present an artificial neural network (ANN) model for the accurate estimation of in-hospital mortality and to demonstrate the validity of the model with real data and a comparison with conventional multiple lin...

Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning.

The Journal of surgical research
BACKGROUND: There is a growing need to identify which bits of information are most valuable for healthcare providers. The aim of this study was to search for the highest impact variables in predicting postsurgery length of stay (LOS) for patients who...

Ensemble machine learning prediction and variable importance analysis of 5-year mortality after cardiac valve and CABG operations.

Scientific reports
Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For long-term mortality, few predictors are known. In th...

Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning.

Communications biology
The clinical treatment planning of coronary heart disease requires hemodynamic parameters to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in the simulation of cardiovascular hemodynamics. However, for the patient-spec...