Presented in part at the Annual Forum of the American College of Veterinary Internal Medicine, Montreal, Canada, June 3–6, 2009. Dr Hart is presently affiliated with University of Minnesota Veterinary Medical Center, 1365 Gortner Avenue, St Paul, MN 55108. Dr Stern is presently affiliated with Department of Veterinary Clinical Sciences, Washington State University, 100 Grimes Way, Pullman, WA 99164. This work was completed at The Ohio State University, Columbus, OH.
Detection of Congestive Heart Failure in Dogs by Doppler Echocardiography
Article first published online: 14 SEP 2010
Copyright © 2010 by the American College of Veterinary Internal Medicine
Journal of Veterinary Internal Medicine
Volume 24, Issue 6, pages 1358–1368, November/December 2010
How to Cite
Schober, K.E., Hart, T.M., Stern, J.A., Li, X., Samii, V.F., Zekas, L.J., Scansen, B.A. and Bonagura, J.D. (2010), Detection of Congestive Heart Failure in Dogs by Doppler Echocardiography. Journal of Veterinary Internal Medicine, 24: 1358–1368. doi: 10.1111/j.1939-1676.2010.0592.x
- Issue published online: 3 NOV 2010
- Article first published online: 14 SEP 2010
- Submitted December 21, 2009; Revised June 30, 2010; Accepted July 20, 2010.
- Degenerative mitral valve disease;
- Dilated cardiomyopathy;
- Respiration rate
Background: Echocardiographic prediction of congestive heart failure (CHF) in dogs has not been prospectively evaluated.
Hypothesis: CHF can be predicted by Doppler echocardiographic (DE) variables of left ventricular (LV) filling in dogs with degenerative mitral valve disease (MVD) and dilated cardiomyopathy (DCM).
Animals: Sixty-three client-owned dogs.
Methods: Prospective clinical cohort study. Physical examination, thoracic radiography, analysis of natriuretic peptides, and transthoracic echocardiography were performed. Diagnosis of CHF was based upon clinical and radiographic findings. Presence or absence of CHF was predicted using receiver-operating characteristic (ROC) curve, multivariate logistic and stepwise regression, and best subsets analyses.
Results: Presence of CHF secondary to MVD or DCM could best be predicted by E : isovolumic relaxation time (IVRT) (area under the ROC curve [AUC]=0.97, P < .001), respiration rate (AUC=0.94, P < .001), Diastolic Functional Class (AUC=0.93, P < .001), and a combination of Diastolic Functional Class, IVRT, and respiration rate (R2=0.80, P < .001) or Diastolic Functional Class (AUC=1.00, P < .001), respiration rate (AUC=1.00, P < .001), and E : IVRT (AUC=0.99, P < .001), and a combination of Diastolic Functional Class and E : IVRT (R2=0.94, P < .001), respectively, whereas other variables including N-terminal pro-brain natriuretic peptide, E : Ea, and E : Vp were less useful.
Conclusion and Clinical Importance: Various DE variables can be used to predict CHF in dogs with MVD and DCM. Determination of the clinical benefit of such variables in initiating, modulating, and assessing success of treatments for CHF needs further study.