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Left ventricular mass-geometry and silent cerebrovascular disease: The Cardiovascular Abnormalities and Brain Lesions

Koki Nakanishi1, Zhezhen Jin2, Shunichi Homma1

  • 1Department of Medicine, Columbia University, New York, NY.

American Heart Journal
|March 8, 2017
PubMed

Insights

Left ventricular hypertrophy, both concentric and eccentric, is linked to silent cerebrovascular disease. These heart conditions increase stroke risk, especially in certain demographics.

Area of Science:

  • Cardiology
  • Neurology
  • Radiology

Background:

  • Abnormal left ventricular (LV) geometric patterns are known prognostic indicators for morbidity and mortality.
  • The association between LV geometric patterns and silent cerebrovascular disease (SCVD) remains underexplored.

Purpose of the Study:

  • To investigate the relationship between different left ventricular geometric patterns and the presence of subclinical cerebrovascular disease.
  • To determine if specific LV geometric patterns are associated with silent brain infarcts (SBIs) and white matter hyperintensity volume (WMHV).

Main Methods:

  • A cohort of 665 participants from the CABL study underwent echocardiography and brain MRI.
  • Participants were categorized into four LV geometric patterns: normal, concentric remodeling, eccentric hypertrophy, and concentric hypertrophy.
  • SCVD was assessed by the presence of SBIs and the volume of WMHV.

Main Results:

  • Concentric hypertrophy showed the highest risk for both SBIs (aOR 3.39) and WMHV (aOR 3.35).
  • Eccentric hypertrophy also demonstrated significant associations with SBIs (aOR 2.52) and WMHV (aOR 1.96).
  • Concentric remodeling was not associated with SCVD. Associations varied across sex, age, and race-ethnic subgroups.

Conclusions:

  • Left ventricular hypertrophy, encompassing both eccentric and concentric patterns, is significantly associated with subclinical cerebrovascular disease in a general, stroke-free population.
  • LV geometric patterns may confer differential risks for SCVD depending on demographic factors such as sex, age, race-ethnicity, and body size.
Abstract

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