Usefulness of Global Longitudinal Strain to Predict Heart Failure Progression in Patients With Nonobstructive

Ethan J Rowin1, Barry J Maron1, Sophie Wells1

  • 1Hypertrophic Cardiomyopathy Center, Division of Cardiology, Tufts Medical Center, Boston, Massachusetts.

Insights

In nonobstructive hypertrophic cardiomyopathy (HC), abnormal global longitudinal strain (GLS) predicts heart failure. Combining GLS with ejection fraction (EF) enhances risk prediction for progressive heart failure in HC patients.

Area of Science:

  • Cardiology
  • Cardiovascular Imaging
  • Heart Failure Research

Background:

  • Predicting prognosis in hypertrophic cardiomyopathy (HC) is crucial for managing disease progression.
  • Reliable markers for heart failure in nonobstructive HC are not well-established.
  • Systolic function assessment is key to understanding HC outcomes.

Purpose of the Study:

  • To evaluate global longitudinal strain (GLS) and other systolic function markers.
  • To identify patients with nonobstructive HC at risk for future heart failure.
  • To assess the predictive value of GLS and ejection fraction (EF) for heart failure progression.

Main Methods:

  • Retrospective analysis of 296 nonobstructive HC patients with preserved ejection fraction (EF).
  • Follow-up for development of progressive heart failure symptoms or systolic dysfunction (EF < 50%).
  • Statistical analysis including logistic regression and reclassification to assess GLS and EF as predictors.

Main Results:

  • Abnormal GLS (< 16%) was associated with a 5-fold increased risk of heart failure.
  • GLS independently predicted heart failure, even after adjusting for EF.
  • Combining GLS and EF significantly improved heart failure prediction (net reclassification improvement 0.55).
  • Patients with GLS < 16% and EF 50-59% had a 12.5-fold higher risk compared to those with GLS > 18% and EF ≥ 60%.

Conclusions:

  • Abnormal GLS is a strong independent predictor of heart failure in nonobstructive HC.
  • Combining GLS with EF provides enhanced prediction of heart failure progression and systolic dysfunction in HC.
  • This combined approach identifies high-risk HC patients needing closer monitoring.

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