Linear, logarithmic, and polynomial models of M-mode echocardiographic measurements in dogs

Am J Vet Res. 2002 Jul;63(7):994-9. doi: 10.2460/ajvr.2002.63.994.

Abstract

Objective: To determine whether logarithmic and polynomial models are superior to simple linear models for predicting reference values for M-mode echocardiographic variables in dogs with a wide range of body weights.

Animals: 69 apparently healthy adult male and female dogs of various breeds, ages (range, 1 to 12 years; median, 3.5 years), and body weights (range, 3.9 to 977 kg; median, 25.4 kg).

Procedure: Echocardiographic M-mode measurements of the interventricular septum, left ventricular dimension (LVD), left ventricular wall, aorta, and left atrium were obtained. Simple linear, second-order polynomial, third-order polynomial, and logarithmic regression models were determined by use of the least-squares method to describe the relationship between M-mode measurements and body weight. Differences in adjusted R2 values of logarithmic and polynomial models were tested for significance of contribution, compared with the simple linear model.

Results: Significant differences in adjusted R2 were found when comparing simple linear with logarithmic or polynomial models for LVD-diastole, LVD-systole, aorta, and left atrium. Differences in adjusted R2 between second-order polynomial, third-order polynomial, and logarithmic models were not significant for any M-mode measurement.

Conclusions and clinical relevance: In this study, logarithmic or second-order polynomial models predicted reference values of M-mode measurements for size of the cardiac chambers better than simple linear models for dogs with a wide range of body weights. Logarithmic and polynomial models were not superior to simple linear models for M-mode measurements of cardiac wall thickness.

Publication types

  • Comparative Study

MeSH terms

  • Animals
  • Dogs / physiology*
  • Echocardiography, Doppler, Color / methods
  • Echocardiography, Doppler, Color / veterinary*
  • Female
  • Heart / physiology*
  • Male
  • Models, Cardiovascular*
  • Reference Values
  • Regression Analysis