AI Article Synopsis

  • * Current guidelines for treating asymptomatic patients focus on heart size and function, but even after surgery, there's still a risk of heart failure and death.
  • * New methods, including machine learning and advanced imaging techniques, are being developed to identify high-risk patients who might benefit from earlier interventions, with valve repair being the preferred treatment.

Article Abstract

Degenerative mitral valve disease is common. Up to a quarter of patients with degenerative mitral valve disease may be asymptomatic despite having severe valve regurgitation. Current guideline indications for intervention in asymptomatic patient are centred on left ventricular dimensions and ejection fraction and may include consideration in atrial fibrillation, pulmonary hypertension and those with left atrial dilatation. However, despite intervention according to these recommendations, patients remain at risk of post-operative heart failure and mortality. Newer risk markers have been developed including left ventricular and atrial strain, myocardial fibrosis demonstrated using late gadolinium enhancement, mitral annular disjunction and ventricular arrhythmia burden. Translating newer markers into clinical practice will require integrating and identifying high-risk phenotypes that benefit from early intervention using machine learning techniques and artificial intelligence. Valve repair is the recommended intervention. However, repair rate and durability are dependent on both operator and centre volumes as well as valve characteristics. Recent advancements, including robotic surgery, may enhance repair rates; however, larger datasets are necessary to confirm these improvements. Efforts should focus on establishing high-volume regional centres of excellence for mitral valve repair.

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Source
http://dx.doi.org/10.1136/heartjnl-2024-324739DOI Listing

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