Long-term outcomes in distinct phenogroups of patients with primary mitral regurgitation undergoing valve surgery

Soongu Kwak1,2, Seung-Ah Lee3, Jaehyun Lim1,2

  • 1Division of Cardiology, Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea (the Republic of).

Abstract

Insights

Researchers identified five distinct patient groups with severe primary mitral regurgitation (MR). These phenogroups have different risk profiles and long-term outcomes after mitral valve surgery, aiding personalized treatment strategies.

Area of Science:

  • Cardiology
  • Medical Research
  • Patient Stratification

Background:

  • Severe primary mitral regurgitation (MR) presents heterogeneous patient profiles and varying risk levels.
  • Understanding these differences is crucial for optimizing treatment and predicting outcomes after mitral valve (MV) surgery.

Purpose of the Study:

  • To identify distinct patient phenogroups within severe primary MR.
  • To investigate the long-term prognosis of these identified phenogroups following MV surgery.

Main Methods:

  • Retrospective analysis of a large cohort of patients with severe primary MR undergoing MV surgery (derivation and validation sets).
  • Latent class analysis using 15 clinical variables to classify patients into subgroups.
  • Primary outcome assessed was all-cause mortality post-MV surgery.

Main Results:

  • Five distinct phenogroups were identified: three younger (varying comorbidities and demographics) and two older (low-risk and high-risk).
  • Significant differences in cumulative survival were observed among phenogroups, with the highest mortality in the high-risk older group (83.4% 5-year survival).
  • The identified phenogroups demonstrated comparable predictive performance to existing scores for degenerative MR.

Conclusions:

  • The study successfully delineated five phenogroups for severe primary MR patients, each with unique risk profiles and prognoses.
  • This phenogrouping approach offers a potential improvement in risk stratification for optimizing surgical timing and intervention strategies in MR patients.

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