Appropriate threshold levels of cardiac beat-to-beat variation in semi-automatic analysis of equine ECG recordings

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Abstract

© 2016 The Author(s). Background: Although premature beats are a matter of concern in horses, the interpretation of equine ECG recordings is complicated by a lack of standardized analysis criteria and a limited knowledge of the normal beat-to-beat variation of equine cardiac rhythm. The purpose of this study was to determine the appropriate threshold levels of maximum acceptable deviation of RR intervals in equine ECG analysis, and to evaluate a novel two-step timing algorithm by quantifying the frequency of arrhythmias in a cohort of he althy adult endurance horses. Results: Beat-to-beat variation differed considerably with heart rate (HR), and an adaptable model consisting of three different HR ranges with separate threshold levels of maximum acceptable RR deviation was consequently defined. For resting HRs < 60 beats/min (bpm) the threshold level of RR deviation was set at 20%, for HRs in the intermediate range between 60 and 100 bpm the threshold was 10%, and for exercising HRs > 100 bpm, the threshold level was 4%. Supraventricular premature beats represented the most prevalent arrhythmia category with varying frequencies in seven horses at rest (median 7, range 2-86) and six horses during exercise (median 2, range 1-24). Conclusions: Beat-to-beat variation of equine cardiac rhythm varies according to HR, and threshold levels in equine ECG analysis should be adjusted accordingly. Standardization of the analysis criteria will enable comparisons of studies and follow-up examinations of patients. A small number of supraventricular premature beats appears to be a normal finding in endurance horses. Further studies are required to validate the findings and determine the clinical significance of premature beats in horses.

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Flethøj, M., Kanters, J. K., Pedersen, P. J., Haugaard, M. M., Carstensen, H., Olsen, L. H., & Buhl, R. (2016). Appropriate threshold levels of cardiac beat-to-beat variation in semi-automatic analysis of equine ECG recordings. BMC Veterinary Research, 12(1). https://doi.org/10.1186/s12917-016-0894-2

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