Redefining Left Ventricular Systolic Dysfunction in Hypertrophic Cardiomyopathy: Ejection Fraction and Global

Soongu Kwak1, Hyung-Kwan Kim1

  • 1Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea; Division of Cardiology, Cardiovascular Center, Seoul National University Hospital, Seoul, Republic of Korea.

Heart Failure Clinics
|October 13, 2025
PubMed

Insights

Hypertrophic cardiomyopathy (HCM) involves thickened heart muscle. Left ventricular global longitudinal strain (LV-GLS) can detect early dysfunction, aiding risk assessment for sudden cardiac death (SCD) in HCM patients.

Area of Science:

  • Cardiology
  • Cardiovascular Imaging
  • Genetics

Background:

  • Hypertrophic cardiomyopathy (HCM) is an inherited cardiac condition.
  • It causes left ventricular (LV) hypertrophy without other identifiable causes.
  • LV systolic dysfunction is linked to symptoms, heart failure, and sudden cardiac death (SCD) risk in HCM.

Purpose of the Study:

  • To evaluate the role of LV global longitudinal strain (LV-GLS) in detecting subclinical LV dysfunction.
  • To assess the potential of integrating LV-GLS with other imaging biomarkers for improved risk stratification in HCM.
  • To explore the utility of LV-GLS for personalized risk assessment in HCM patients.

Main Methods:

  • Utilizing echocardiography to measure LV global longitudinal strain (LV-GLS).
  • Analyzing late gadolinium enhancement (LGE) and left atrial reservoir strain (LARS) as complementary imaging biomarkers.
  • Correlating LV-GLS findings with clinical outcomes and risk factors for SCD.

Main Results:

  • LV-GLS is a sensitive indicator of subclinical left ventricular systolic dysfunction in HCM.
  • Integration of LV-GLS with LGE and LARS may enhance the prediction of adverse events.
  • LV-GLS shows promise for refining risk stratification in hypertrophic cardiomyopathy.

Conclusions:

  • LV-GLS is a valuable tool for assessing cardiac function in HCM.
  • Combined imaging biomarkers, including LV-GLS, can improve risk prediction models.
  • Further research is needed to establish definitive LV-GLS cutoffs for personalized HCM management.

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