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Related Concept Videos

Mitral Regurgitation II: Clinical Features and Diagnostic Tests01:23

Mitral Regurgitation II: Clinical Features and Diagnostic Tests

28
Mitral regurgitation (MR) is a valvular heart disorder in which the mitral valve fails to close tightly, allowing blood to leak backward into the heart. Understanding the clinical manifestations, assessment, diagnostic findings, and medical management of MR is crucial to effectively managing affected patients.Clinical Manifestations of Mitral RegurgitationMitral regurgitation can be acute or chronic, each presenting differently and requiring different approaches:1. Acute Mitral...
28
Mitral Regurgitation I: Introduction01:20

Mitral Regurgitation I: Introduction

23
Mitral regurgitation is characterized by the backward circulation of blood from the left ventricle to the left atrium during systole, a phase of the cardiac cycle when the heart contracts and pumps blood out of the chambers. This abnormal flow occurs primarily due to the dysfunction of the mitral valve or its supporting structures, which include the mitral leaflets, chordae tendineae, annulus, and papillary muscles.Etiology and Mechanisms:Primary Mitral Regurgitation: This type arises from...
23
Mitral Regurgitation III: Medical Management01:25

Mitral Regurgitation III: Medical Management

21
Mitral regurgitation (MR) is characterized by retrograde blood circulation from the left ventricle into the left atrium due to inadequate mitral valve closure. The severity of the condition, symptoms, and underlying cause determine treatment strategies.Monitoring and Pharmacological TreatmentPatients with mild to moderate MR typically do not need immediate intervention but regular monitoring to assess progression and guide treatment. Patients with mild MR should have an echocardiogram every 3-5...
21
Mitral Valve Prolapse II: Assessment and Management01:22

Mitral Valve Prolapse II: Assessment and Management

28
IntroductionA range of clinical features characterizes Mitral Valve Prolapse (MVP), but it is important to note that many individuals with MVP are asymptomatic and may remain so throughout their lives. For those who do exhibit symptoms, the following are the key clinical features:Palpitations: This is a common symptom where individuals feel an irregular or rapid heartbeat. Palpitations in MVP are often due to arrhythmias such as premature ventricular contractions or supraventricular...
28
Mitral Regurgitation IV: Nursing Management01:28

Mitral Regurgitation IV: Nursing Management

52
Mitral regurgitation (MR) is a condition where the mitral valve does not close properly, leading to the backward flow of blood from the left ventricle into the left atrium during systole. This condition can arise from various causes, including rheumatic fever, infective endocarditis, or degenerative valve disease. Effective nursing management is crucial to optimizing patient outcomes and involves comprehensive assessment and targeted interventions.Comprehensive Patient AssessmentA detailed...
52
Mitral Stenosis II: Clinical features and Diagnostic Tests01:23

Mitral Stenosis II: Clinical features and Diagnostic Tests

27
Mitral stenosis is a heart condition in which the mitral valve, which allows blood to flow from the left atrium to the left ventricle, becomes narrowed or stenotic. This narrowing hinders blood flow and leads to clinical symptoms requiring specific medical evaluations and management strategies. The following overview outlines the clinical symptoms, assessments, diagnostic findings, prevention methods, and treatments for mitral stenosis.Clinical ManifestationsDyspnea (shortness of breath): This...
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Related Experiment Video

Updated: Jul 31, 2025

An Image Guided Transapical Mitral Valve Leaflet Puncture Model of Controlled Volume Overload from Mitral Regurgitation in the Rat
07:42

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Understanding post-surgical decline in left ventricular function in primary mitral regurgitation using regression and

Jingyi Zheng1, Yuexin Li1, Nedret Billor1

  • 1Department of Mathematics and Statistics, Auburn University, Auburn, AL, United States.

Frontiers in Cardiovascular Medicine
|May 8, 2023
PubMed
Summary

Machine learning models predict post-surgery low left ventricular ejection fraction (LVEF) in primary mitral regurgitation (PMR) patients. Cardiac magnetic resonance (CMR) parameters like LV sphericity index and strain rate improve prediction accuracy.

Keywords:
LV circumferential strain ratemachine learningmitral regurgitation (MR)post-surgical LVEFpredictive models

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Last Updated: Jul 31, 2025

An Image Guided Transapical Mitral Valve Leaflet Puncture Model of Controlled Volume Overload from Mitral Regurgitation in the Rat
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Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Machine Learning

Background:

  • Class I echocardiographic guidelines for primary mitral regurgitation (PMR) risk low left ventricular ejection fraction (LVEF) <50% post-surgery, even with pre-surgical LVEF >60%.
  • No current models predict post-surgery LVEF <50% in PMR, considering the complex interplay of preload and ejection dynamics.
  • Cardiac magnetic resonance (CMR) offers advanced imaging for assessing left ventricular (LV) remodeling and function.

Purpose of the Study:

  • To develop and validate regression and machine learning models for predicting post-surgery LVEF <50% in PMR patients.
  • To identify key CMR-derived LV remodeling and function parameters that predict adverse post-surgical LVEF.
  • To assess the predictive performance of different machine learning algorithms.

Main Methods:

  • CMR with tissue tagging was performed on 51 pre-surgery PMR patients, 49 asymptomatic PMR patients, and age-matched controls.
  • Machine learning models including LASSO, Random Forest (RF), XGBoost, and SVM were trained and validated on pre-surgery PMR patients.
  • Recursive feature elimination and LASSO were used to reduce model complexity. Stratified cross-validation and 100 data splits minimized overfitting.

Main Results:

  • Thirteen (24.5%) pre-surgery PMR patients developed LVEF <50% post-surgery.
  • Predictors of post-surgery LVEF <50% included LVEF, LV sphericity index, and LV mid-systolic circumferential strain rate.
  • The RF model achieved 86.17% accuracy in predicting post-surgery LVEF <50%, outperforming logistic regression (77.92%).

Conclusions:

  • LV sphericity index and circumferential strain rate are potential predictors of post-surgical LVEF in PMR.
  • Machine learning models, particularly RF, demonstrate high accuracy in predicting post-surgery LVEF <50%.
  • Further longitudinal studies are warranted to validate these findings and refine predictive models for PMR patients undergoing mitral valve surgery.