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Home » Archive » 2019

TDK conference 2019

Physiological arythmias in horses and its effect on resting HRV measurements
Sebők Zita - year 6
University of Veterinary Medicine Budapest, Department Animal Breeding, Nutrition and Laboratory Animal Science
Supervisor: Dr. Orsolya Korbacska-Kutasi

Abstract:

Cardiac function is countinously responding to the neurohormonal influences and thanks to that, it can perfectly adapt to the actual enviromental stimuli. The heart rate variability (HRV) is the difference between two heart beats’ interval, which is controlled by the autonomous nervous system. Heart rate variability measurement is a non-invasive method which enables us to examine and distinguish the activity of the sympathetic and parasympathetic nervous system, and also to determine the rate of the two measured parameter.

Studies from recent years showed that HRV can be an indicator of a horse’s training status. However in the resting horse, arythmias caused by high vagal tone makes the measurements and evaluation much more difficult.

The aim of this study was to eveluate the changes in HRV parameters after deleting the arythmic phases caused by the physiologycal parasympaticotony. In our research we were able to cut 3-3-minute phases with and without physiological arythmias from 30 minutes long ECG-recordings of 50 horses. It was very important that all of the recordings had to be artefact-free. Then these cut-off phases were put into an HRV analysing program (Kubios). Firstly the samples were examined without any correction filter. The changes in HRV parameters from the arythmic and non-arythmic phases were analyzed by a paired t-test. As a result we found differences in HR max, SNS index and Stress index. The p value of pNN50 parameter was very close to the level of significance (p=0,05316). The pNN50 is the percentage of the number of pairs of successive R-R intervals that differ by more than 50 ms. In the correction-free test the HR max value showed significant difference between the arythmic and non-arythmic phases. At the end, the results were higher in the arythmic group. Considering the data from the SNS and Stress Index, the parameters were simultanious, since during the examination of the non- arhytmic phases, the values of the SNS index were 74% higher than the values of the arythmic phases, while this rate was 78% in the case of Stress index. According to these rates we can claim, that in the arythmic phases the parasymypmathetic, while in the non-arythmic phases the sympathetic nervous system was dominant.

In conclusion, in spite of the parameters with significant differences, the program can also be used in the cases of horses with phisiological arhytmias, even for making an HRV-based training plan because when we compared the parameters generally used for HRV analysis such as LF, HF, LF/HF, RMSSD, Mean RR we did not find any statistically significant difference.



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