Abstract 3847: Impedance Cardiography (ICG) Identifies Subclinical Systolic Dysfunction Associated with Obesity: A Population-Based Study
Backgroud: Obesity is independently associated with incident heart failure (HF), but only recent studies with sophisticated echocardiographic methods demonstrated subclinical systolic abnormalities in obese subjects without HF or low ejection fraction. Such techniques provide important markers of subclinical disease but are difficult to implement in large-scale studies or clinical practice. ICG represents an easily applied, operator-independent tool to assess cardiac function. We aimed to determine whether abnormalities of systolic function can be identified in obese subjects with the use of ICG.
Methods: We studied 310 adults aged 20 – 80 years who were unmedicated and free of diabetes or HF as part of a population-based study. ICG was performed with the Bio-Z device (Cardiodynamics; San Diego, CA). Simple and multiple regression were used to identify associations between body mass index (BMI) and the systolic acceleration index (ACI) and velocity index (VI). To allow direct comparisons, all reported regression coefficients are standardized.
Resuts: Highly significant univariate negative correlations between BMI and VI (R = −0.56; p < 0.0001) and between BMI and ACI (R = −0.51; p < 0.0001) were found. After adjustment for age, gender, HDL and LDL cholesterol, triglycerides, heart rate, systolic and diastolic blood pressure and stroke volume, BMI remained an independent negative predictor of both VI (β = −0.48; R2 increase = 0.18; p < 0.0001) and AI (β = −0.43; R2 increase = 0.14; p < 0.0001). The correlation was also independent of systemic arterial compliance and baseline impedance. In multivariate models BMI was the strongest predictor of both parameters. The adjusted partial correlation coefficients with BMI were −0.47 for AI and −0.56 for VI (both p < 0.0001). Interestingly, lower HDL levels also predicted lower AI and VI (independenty of BMI), suggesting that metabolic components may play a role in these abnormalities.
Conclusions: ICG readily identifies subclinical systolic abnormalities associated with obesity, and may provide an easily applied tool for early detection of subclinical cardiac changes associated with obesity and to evaluate their natural history and response to interventions.