Left heart chamber quantification in obese patients: how does larger body size affect echocardiographic measurements?
Academic Article
Overview
abstract
BACKGROUND: Accurate normalization of cardiac chamber size in the obese population is a challenge. The aim of this study was to develop and assess the performance of allometric models for scaling left heart chamber sizes, including left atrial anteroposterior dimension (LADAP), left atrial volume (LAV), left ventricular end-diastolic volume (LVEDV), and left ventricular end-diastolic dimension (LVEDD), in an obese population. METHODS: To normalize left heart chamber measurements (Y: LADAP, LAV, LVEDV, and LVEDD) to body size variables (X: height, weight, body mass index, and body surface area), both isometric models (Y = aX) and optimal allometric models (Y = aX(b)) were tested. A logarithmic transformation (LnY = Lna + b × LnX) and ordinary least squares linear regression was performed to estimate the allometric scaling exponents. Pearson's correlation coefficients were obtained for measured and indexed left chamber sizes using both isometric and allometric models against body size variables. Gender-specific allometric models were also derived as sensitivity analyses. RESULTS: A total of 717 healthy obese subjects were included in the analysis. The mean body surface area and body mass index were 2.3 m(2) and 42.2 kg/m(2), respectively. Measured LADAP, LAV, LVEDD, and LVEDV were positively correlated with body size variables. Allometric scaling of LADAP, LAV, LVEDD, and LVEDV showed stronger correlation with measured chamber sizes compared with isometric scaling. The overcorrection caused by isometric scaling significantly improved after allometric models were used. The sensitivity analysis showed no significant differences in scaling exponents between men and women. CONCLUSIONS: Normalizing cardiac chamber measurements with allometric scaling methods is superior to the use of isometric methods in removing the effects of body size and minimizing overcorrection in the obese population. Using an allometric model with height provides the most accurate results.
