Advanced electrocardiographic parameters change with severity of mitral regurgitation in Cavalier King Charles
M Spiljak Pakkanen1, A Domanjko Petrič, L H Olsen
1Institute of Physiology, Medical Faculty, Ljubljana, Slovenia.
Insights
Advanced resting ECG (A-ECG) parameters show promise in predicting mitral regurgitation (MR) severity in Cavalier King Charles Spaniels. While A-ECG improves prediction beyond traditional measures, its clinical utility requires further investigation.
Area of Science:
- Veterinary Cardiology
- Advanced Electrocardiography
- Canine Cardiac Disease
Background:
- Advanced resting electrocardiography (A-ECG) enhances diagnostic capabilities for cardiac conditions.
- Early detection of cardiac disease is crucial, even before clinical signs manifest.
Purpose of the Study:
- To identify A-ECG parameters that correlate with mitral regurgitation (MR) severity in Cavalier King Charles Spaniels (CKCSs).
- To assess the predictive value of A-ECG parameters in dogs with myxomatous mitral valve disease (MMVD).
Main Methods:
- Seventy-six CKCSs with varying degrees of MR were prospectively studied.
- 12-lead A-ECG recordings were analyzed using custom software to derive conventional and A-ECG parameters.
- MR severity was quantified by color Doppler mapping.
Main Results:
- Nineteen out of 76 ECG parameters showed significant differences across MR severity groups.
- A 4-parameter A-ECG model (heart rate variability, QT variability, QRS amplitude) explained 82.4% of variance in MR severity.
- Including age and murmur grade further improved predictive accuracy (R=0.74 to 0.85).
Conclusions:
- Selected A-ECG parameters offer improved prediction of MR severity in CKCSs with sinus rhythm.
- The current predictive increment may not yet justify widespread clinical adoption in veterinary practice.
- Further research is needed to optimize A-ECG application for canine cardiac disease.
Background:
Multiple advanced resting ECG (A-ECG) techniques have improved the diagnostic or prognostic value of ECG in detecting human cardiac diseases even before onset of clinical signs or changes in conventional ECG.
Objective:
To determine which A-ECG parameters, derived from 12-lead A-ECG recordings, change with severity of mitral regurgitation (MR) caused by myxomatous mitral valve disease (MMVD) in Cavalier King Charles Spaniels (CKCSs) in sinus rhythm.
Animals:
Seventy-six privately owned CKCSs.
Methods:
Dogs were prospectively divided into 5 groups according to the degree of MR (estimated by color Doppler mapping as the percentage of the left atrial area affected by the MR jet) and presence of clinical signs. High fidelity approximately 5-minute 12-lead ECG recordings were evaluated using custom software to calculate multiple conventional and A-ECG parameters.
Results:
Nineteen of 76 ECG parameters were significantly different (P < .05) across the 5 dog groups. A 4-parameter model that incorporated results from 1 parameter of heart rate variability, 2 parameters of QT variability, and 1 parameter of QRS amplitude was identified that explained 82.4% of the variance with a correlation coefficient (R) of 0.60 (P < .01). When age or murmur grade was included in the statistical model the prediction value further increased the R to 0.74 and 0.85 (P < .01), respectively.
Conclusion:
In CKCSs with sinus rhythm, 4 selected A-ECG parameters further improve prediction of MR jet severity beyond age and murmur grade, although the predictive increment in this study probably is not sufficient to warrant utilization in clinical veterinary practice.
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