AIMC Topic: Transcatheter Aortic Valve Replacement

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Deep learning-based prediction of early cerebrovascular events after transcatheter aortic valve replacement.

Scientific reports Sep 21, 2021
Cerebrovascular events (CVE) are among the most feared complications of transcatheter aortic valve replacement (TAVR). CVE appear difficult to predict due to their multifactorial origin incompletely explained by clinical predictors. We aimed to build...
Humans Prospective Studies Tomography, X-Ray Computed Male Deep Learning Incidence Stroke Transcatheter Aortic Valve Replacement Female Risk Factors Aged Aged, 80 and over
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Predicting Infective Endocarditis After Transcatheter Aortic Valve Implantation Via a Risk Model.

The American journal of cardiology May 9, 2021
Endocarditis Transcatheter Aortic Valve Replacement Postoperative Complications United States Age Factors Predictive Value of Tests Humans Machine Learning Female Risk Factors Male
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Machine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement.

Circulation. Arrhythmia and electrophysiology Mar 9, 2021
Humans Machine Learning Decision Support Techniques Heart Rate Transcatheter Aortic Valve Replacement Pacemaker, Artificial Treatment Outcome Atrioventricular Block Action Potentials Prospective Studies Aortic Valve Retrospective Studies Predictive Value of Tests Risk Factors Cardiac Pacing, Artificial Risk Assessment
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Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

Pacing and clinical electrophysiology : PACE Jan 28, 2021
BACKGROUND: An accurate assessment of permanent pacemaker implantation (PPI) risk following transcatheter aortic valve replacement (TAVR) is important for clinical decision making. The aims of this study were to investigate the significance and utili...
Aged Aged, 80 and over Male Risk Assessment Postoperative Complications Machine Learning Forecasting Retrospective Studies Female Prosthesis Implantation Pacemaker, Artificial Logistic Models Aortic Valve Stenosis Arrhythmias, Cardiac Transcatheter Aortic Valve Replacement Humans
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Usefulness of Semisupervised Machine-Learning-Based Phenogrouping to Improve Risk Assessment for Patients Undergoing Transcatheter Aortic Valve Implantation.

The American journal of cardiology Sep 15, 2020
Semisupervised machine-learning methods are able to learn from fewer labeled patient data. We illustrate the potential use of a semisupervised automated machine-learning (AutoML) pipeline for phenotyping patients who underwent transcatheter aortic va...
Aged, 80 and over Male Risk Assessment Severity of Illness Index Cohort Studies Treatment Outcome Humans Aortic Valve Stenosis Machine Learning Transcatheter Aortic Valve Replacement Phenotype Female Aged
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Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

The Annals of thoracic surgery Jul 17, 2020
BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).
Aortic Valve Stenosis Aortic Valve Education, Medical, Graduate Transcatheter Aortic Valve Replacement Humans Machine Learning Algorithms Prognosis Female Aged Male ROC Curve
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Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI.

Clinical research in cardiology : official journal of the German Cardiac Society Jun 24, 2020
BACKGROUND: Currently, patient selection in TAVI is based upon a multidisciplinary heart team assessment of patient comorbidities and surgical risk stratification. In an era of increasing need for precision medicine and quickly expanding TAVI indicat...
Humans Machine Learning Retrospective Studies Female Risk Factors Aged, 80 and over Survival Rate Male Risk Assessment Transcatheter Aortic Valve Replacement Inpatients Postoperative Complications Cause of Death Time Factors Morbidity Hospital Mortality Heart Valve Diseases Aortic Valve Germany
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Robotic transcatheter aortic valve replacement with magnetic resonance imaging is feasible in animal models, but is it feasible in patients?

The Journal of thoracic and cardiovascular surgery Jan 7, 2016
Heart Valve Prosthesis Implantation Models, Animal Heart Valve Prosthesis Cardiac Catheterization Transcatheter Aortic Valve Replacement Magnetic Resonance Imaging Aortic Valve Stenosis Aortic Valve Robotics Humans Animals Treatment Outcome
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AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Future cardiology Jun 1, 2025
BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following...
Female Risk Factors Aged Humans Risk Assessment Aged, 80 and over Transcatheter Aortic Valve Replacement Postoperative Complications Male Bundle-Branch Block Machine Learning Electrocardiography Algorithms Aortic Valve Stenosis Retrospective Studies
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Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach.

BMC cardiovascular disorders May 10, 2025
BACKGROUND: Post-operative moderate-to-severe mitral regurgitation (MR) following transcatheter aortic valve replacement (TAVR) is associated with poor outcomes, yet the factors contributing to this complication are not well understood. This study ai...
Risk Assessment Female Aortic Valve Stenosis Humans Severity of Illness Index Predictive Value of Tests Risk Factors Machine Learning Time Factors Aged Mitral Valve Decision Support Techniques Treatment Outcome Mitral Valve Insufficiency Aged, 80 and over Retrospective Studies Transcatheter Aortic Valve Replacement Male
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