ADVANCED ELECTROCARDIOGRAPHY CAN PREDICT MITRAL REGURGITATION IN CAVALIER KING CHARLES SPANIELS WITH MYXOMATOUS MITRAL VALVE DISEASE. M Spiljak1, AD Petric2, LH Olsen3, A Stepancic4, T Falk3, CE Rasmussen3, V Starc1. 1. Institute of Physiology, Medical Faculty, University of Ljubljana, Slovenia. 2. Clinic for Surgery and Small Animal Medicine, Veterinary Faculty, University of Ljubljana, Slovenia. 3. Department of Basic Animal and Veterinary Sciences, Faculty of Life Sciences, University of Copenhagen, Denmark. 4. Quality Control Department, Metallurgical and Chemical Industry Cinkarna Celje, INC., Slovenia
Recently, multiple advanced resting electrocardiographic (ECG) techniques have been applied in humans for detection of cardiac autonomic and repolarisation function. This has improved the diagnostic and/or prognostic value of short-time ECG in detection of common human cardiac diseases even before onset of symptoms or changes in the standard ECG. Therefore, this study investigates, if advanced ECG can predict the severity of mitral regurgitation (MR) in dogs with myxomatous mitral valve disease (MMVD) and thereby improve the diagnostic value of ECG.
The study included 77 privately owned Cavalier King Charles Spaniels (CKCSs) (age 6.0 ± 2.7 years; 30 males and 47 females). All dogs were examined by echocardiography and a short-time (3-5 min) high-fidelity 12-lead ECG, with the dog in a resting position and in sinus rhythm. Dogs were divided into 5 groups according to the degree of MR estimated as the percentage of the left atrium area using color Doppler mapping (0%; 0% < jet = 15%; 15% < jet = 50%; jet > 50%; jet = 100% and with clinical signs of congestive heart failure). ECG recordings were evaluated via custom software programs to calculate 76 different parameters, including heart rate variability (HRV), QT variability (QTV), T-wave complexity, wave morphology and 3-D ECG. One-way ANOVA determined 21 ECG parameters, which were significantly different (P < 0.05) between the 5 dog groups. Principal component factor analysis identified a 5-factor model with 83.2% explained variability. QRS dipolar voltage and two repolarization indices of QTV increased significantly with MR severity, whereas total power of the frequency spectrum of RR interval and the standard deviation of QTV decreased significantly with MR severity. For the 5 selected parameters the prediction of MR jet value was tested by multiple linear regression. A correlation coefficient (R) of 0.65 indicated that the prediction value was significant (P < 0.01). If age was included in the multiple linear regression the prediction value was further increased (R = 0.80).
Our results indicate that for a cut-off criteria of MR = 50% jet the five selected ECG parameters could predict the severity of MR caused by MMVD in CKCSs with sinus rhythm with sensitivity 65% (78% with age inclusion) and specificity 98% (92% with age inclusion) (P < 0.05).