Markers of increased risk in primary mitral regurgitation

Abstract Background The indication for surgery in patients with severe primary mitral regurgitation (MR) is currently based on the presence of symptoms, left ventricular (LV) dilatation and dysfunction, atrial fibrillation and pulmonary hypertension. The aim of this study was to evaluate the prognostic impact of a new staging classification based on cardiac damage including the known risk factors but also including global longitudinal strain (GLS), severe left atrial (LA) dilatation and right ventricular (RV) dysfunction. Methods In total 614 patients who underwent surgery for severe primary MR with available baseline transthoracic echocardiograms were included. Patients were classified according to the extent of cardiac damage (Figure): Stage 0-no cardiac damage, Stage 1-LV damage, Stage 2-LA damage, Stage 3-pulmonary vasculature or tricuspid valve damage and Stage 4-RV damage. Patients were followed for all-cause mortality. Results Based on the proposed classification, 172 (28%) patients were classified as Stage 0, 102 (17%) as Stage 1, 134 (21%) as Stage 2, 135 (22%) as Stage 3 and 71 (11%) as Stage 4. The more advanced the stage, the older the patients were with worse kidney function, more symptoms and higher EuroScore. Kaplan-Meier curve analysis revealed that patients with more advanced stages of cardiac damage had a significantly worse survival (log-rank chi-square 35.2; p<0.001) (Figure). On multivariable analysis, age, male, chronic obstructive pulmonary disease, kidney function, and stage of cardiac damage were independently associated with all-cause mortality. For each stage increase, a 22% higher risk for all-cause mortality was observed (95% CI: 1.064–1.395; p=0.004). Conclusion In patients with severe primary MR, a novel staging classification based on the extent of cardiac damage, may help refining risk stratification, particularly including also GLS, LA dilatation and RV dysfunction in the assessment. Funding Acknowledgement Type of funding source: None

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CAN MACHINE LEARNING MODELS HELP US PREDICT POSTOPERATIVE OUTCOMES IN PRIMARY MITRAL REGURGITATION

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(21)03084-9 ◽

2021 ◽

Vol 77 (18) ◽

pp. 1728

Author(s):

Efstathia Andrikopoulou ◽

Ye Li ◽

Jingyi Zheng ◽

Thomas Denney ◽

Betty Pat ◽

...

Keyword(s):

Machine Learning ◽

Mitral Regurgitation ◽

Postoperative Outcomes ◽

Learning Models ◽

Primary Mitral Regurgitation ◽

Machine Learning Models

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Importance of Exercise Capacity in Predicting Outcomes and Determining Optimal Timing of Surgery in Significant Primary Mitral Regurgitation

Journal of the American Heart Association ◽

10.1161/jaha.114.001010 ◽

2014 ◽

Vol 3 (5) ◽

Cited By ~ 14

Author(s):

Peyman Naji ◽

Brian P. Griffin ◽

Tyler Barr ◽

Fadi Asfahan ◽

A. Marc Gillinov ◽

...

Keyword(s):

Mitral Regurgitation ◽

Exercise Capacity ◽

Timing Of Surgery ◽

Optimal Timing ◽

Primary Mitral Regurgitation

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Left ventricular contractile reserve in asymptomatic primary mitral regurgitation

European Heart Journal ◽

10.1093/eurheartj/eht345 ◽

2013 ◽

Vol 35 (24) ◽

pp. 1608-1616 ◽

Cited By ~ 68

Author(s):

Julien Magne ◽

Haifa Mahjoub ◽

Raluca Dulgheru ◽

Philippe Pibarot ◽

Luc. A. Pierard ◽

...

Keyword(s):

Mitral Regurgitation ◽

Left Ventricular ◽

Contractile Reserve ◽

Primary Mitral Regurgitation

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Characterization of Degenerative Mitral Valve Disease: Differences between Fibroelastic Deficiency and Barlow’s Disease

Journal of Cardiovascular Development and Disease ◽

10.3390/jcdd8020023 ◽

2021 ◽

Vol 8 (2) ◽

pp. 23

Author(s):

Aniek L. van Wijngaarden ◽

Boudewijn P. T. Kruithof ◽

Tommaso Vinella ◽

Daniela Q. C. M. Barge-Schaapveld ◽

Nina Ajmone Marsan

Keyword(s):

Mitral Valve ◽

Mitral Regurgitation ◽

Mitral Valve Disease ◽

Patient Management ◽

Valve Disease ◽

Common Cause ◽

Barlow’S Disease ◽

Primary Mitral Regurgitation ◽

Fibroelastic Deficiency

Degenerative mitral valve disease causing mitral valve prolapse is the most common cause of primary mitral regurgitation, with two distinct phenotypes generally recognized with some major differences, i.e., fibroelastic deficiency (FED) and Barlow’s disease. The aim of this review was to describe the main histological, clinical and echocardiographic features of patients with FED and Barlow’s disease, highlighting the differences in diagnosis, risk stratification and patient management, but also the still significant gaps in understanding the exact pathophysiology of these two phenotypes.

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Abstract 13745: Severity of Functional Mitral Regurgitation During Maximal Exercise Testing in Heart Failure: Additional Value of Combining Echocardiography with Cardiopulmonary Exercise Testing

Circulation ◽

10.1161/circ.130.suppl_2.13745 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Greta Generati ◽

Francesco Bandera ◽

Marta Pellegrino ◽

Valentina Labate ◽

Eleonora Alfonzetti ◽

...

Keyword(s):

Heart Failure ◽

Mitral Regurgitation ◽

Ejection Fraction ◽

Exercise Testing ◽

Cardiopulmonary Exercise Testing ◽

Functional Mitral Regurgitation ◽

Peak Exercise ◽

Cardiopulmonary Exercise ◽

Pulmonary Hemodynamic ◽

Increased Risk

Background: In heart failure (HF) patients the severity of mitral regurgitation (MR) at rest has a well established prognostic value and its increase during exercise further adds to an increased risk. Our goal was to define the relationship between the degree of exercise MR severity with cardiopulmonary and echocardiographic related phenotypes in a cohort of HF patients. Methods: 71 HF reduced ejection fraction patients (mean age 67±11; male 72%; ischemic etiology 61%; NYHA class I, II, III and IV 13%, 36%, 39% and 12%, mean ejection fraction 33±9%) underwent cardiopulmonary exercise test (CPET) on tiltable cycle-ergometer combined with echocardiography at rest and during exercise. The population was divided into two groups according to the degree of functional peak MR: no to mild/moderate MR (no MR, MR1+ and MR2+) vs moderate/severe MR (MR3+ and MR4+). Results: A good correlation (ρ coefficient= 0.49) was found between the degree of dynamic MR and PASP at peak exercise. Despite similar echocardiographic profile at rest patients with significant peak MR (MR≥3+) had worse exercise performance (lower peak VO2, O2 pulse and workload) and impaired ventilatory efficiency (higher VE/VCO2 slope). Conclusions: In HF patients the severity of exercise-induced MR is associated with the most unfavorable performance and pulmonary hemodynamic response. A combined approach with CPET and echocardiographic assessment can help to early unmask and target functional MR and its related unfavorable phenotypes.

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