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Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study.

Publication ,  Journal Article
Selvaraj, S; Aguilar, FG; Martinez, EE; Beussink, L; Kim, K-YA; Peng, J; Rasmussen-Torvik, L; Sha, J; Irvin, MR; Gu, CC; Lewis, CE; Hunt, SC ...
Published in: J Am Heart Assoc
April 29, 2014

BACKGROUND: Comorbidities are common in heart failure (HF), and the number of comorbidities has been associated with poor outcomes in HF patients. However, little is known about the effect of multiple comorbidities on cardiac mechanics, which could impact the pathogenesis of HF. We sought to determine the relationship between comorbidity burden and adverse cardiac mechanics. METHODS AND RESULTS: We performed speckle-tracking analysis on echocardiograms from the HyperGEN study (n=2150). Global longitudinal, circumferential, and radial strain, and early diastolic (e') tissue velocities were measured. We evaluated the association between comorbidity number and cardiac mechanics using linear mixed effects models to account for relatedness among subjects. The mean age was 51 ± 14 years, 58% were female, and 47% were African American. Dyslipidemia and hypertension were the most common comorbidities (61% and 58%, respectively). After adjusting for left ventricular (LV) mass index, ejection fraction, and several potential confounders, the number of comorbidities remained associated with all indices of cardiac mechanics except global circumferential strain (eg, β=-0.32 [95% CI -0.44, -0.20] per 1-unit increase in number of comorbidities for global longitudinal strain; β=-0.16 [95% CI -0.20, -0.11] for e' velocity; P ≤ 0.0001 for both comparisons). Results were similar after excluding participants with abnormal LV geometry (P<0.05 for all comparisons). CONCLUSIONS: Higher comorbidity burden is associated with worse cardiac mechanics, even in the presence of normal LV geometry. The deleterious effect of multiple comorbidities on cardiac mechanics may explain both the high comorbidity burden and adverse outcomes in patients who ultimately develop HF.

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Published In

J Am Heart Assoc

DOI

EISSN

2047-9980

Publication Date

April 29, 2014

Volume

3

Issue

3

Start / End Page

e000631

Location

England

Related Subject Headings

  • White People
  • Stroke Volume
  • Risk Factors
  • Middle Aged
  • Male
  • Image Interpretation, Computer-Assisted
  • Hypertension
  • Humans
  • Heart Ventricles
  • Heart Failure
 

Citation

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Selvaraj, S., Aguilar, F. G., Martinez, E. E., Beussink, L., Kim, K.-Y., Peng, J., … Shah, S. J. (2014). Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study. J Am Heart Assoc, 3(3), e000631. https://doi.org/10.1161/JAHA.113.000631
Selvaraj, Senthil, Frank G. Aguilar, Eva E. Martinez, Lauren Beussink, Kwang-Youn A. Kim, Jie Peng, Laura Rasmussen-Torvik, et al. “Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study.J Am Heart Assoc 3, no. 3 (April 29, 2014): e000631. https://doi.org/10.1161/JAHA.113.000631.
Selvaraj S, Aguilar FG, Martinez EE, Beussink L, Kim K-YA, Peng J, et al. Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study. J Am Heart Assoc. 2014 Apr 29;3(3):e000631.
Selvaraj, Senthil, et al. “Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study.J Am Heart Assoc, vol. 3, no. 3, Apr. 2014, p. e000631. Pubmed, doi:10.1161/JAHA.113.000631.
Selvaraj S, Aguilar FG, Martinez EE, Beussink L, Kim K-YA, Peng J, Rasmussen-Torvik L, Sha J, Irvin MR, Gu CC, Lewis CE, Hunt SC, Arnett DK, Shah SJ. Association of comorbidity burden with abnormal cardiac mechanics: findings from the HyperGEN study. J Am Heart Assoc. 2014 Apr 29;3(3):e000631.
Journal cover image

Published In

J Am Heart Assoc

DOI

EISSN

2047-9980

Publication Date

April 29, 2014

Volume

3

Issue

3

Start / End Page

e000631

Location

England

Related Subject Headings

  • White People
  • Stroke Volume
  • Risk Factors
  • Middle Aged
  • Male
  • Image Interpretation, Computer-Assisted
  • Hypertension
  • Humans
  • Heart Ventricles
  • Heart Failure