B H Eggensperger1, C C Schwarzwald2. 1. Clinic for Equine Internal Medicine, Equine Department, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland. 2. Clinic for Equine Internal Medicine, Equine Department, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland. Electronic address: cschwarzwald@vetclinics.uzh.ch.
Abstract
OBJECTIVES: To assess the influence of 2nd-degree AV blocks (AVB) on RR interval-based heart rate variability (HRV) variables; to investigate the effect of using PP interval time series and of artifact filtering on HRV analyses; to investigate the influence of electrocardiogram (ECG) recording length and time of recording; and to calculate day-to-day variability and reference intervals of HRV variables. ANIMALS: Thirty healthy adult horses. METHODS: RR and PP interval time series were extracted from 10-h Holter ECGs and an automated filter was applied to the RR time series (RRf). Time-domain HRV variables were calculated based on RR, PP, and RRf time series and their relation to the number of AVBs was assessed. Hourly 10- and 60-min segments were extracted to investigate the influence of segment length and recording time on HRV variables. Day-to-day variability and reference intervals of HRV variables were calculated. RESULTS: Variables of short-term HRV were significantly influenced by the number of AVBs when based on RR, but not when based on PP- and RRf time series. PP- and RRf-based HRV variables were in good agreement. The majority of HRV variables were influenced by recording time and ECG segment length. Day-to-day variability of HRV variables was low when based on 10-h ECG recordings but moderate to high when based on 60-min and 10-min recordings. CONCLUSIONS: Second-degree AVBs significantly influence conventional RR-based, but not PP- and RRf-based time-domain HRV variables. However, PP and RRf analyses have limitations and recording length and time of recording must be considered.
OBJECTIVES: To assess the influence of 2nd-degree AV blocks (AVB) on RR interval-based heart rate variability (HRV) variables; to investigate the effect of using PP interval time series and of artifact filtering on HRV analyses; to investigate the influence of electrocardiogram (ECG) recording length and time of recording; and to calculate day-to-day variability and reference intervals of HRV variables. ANIMALS: Thirty healthy adult horses. METHODS: RR and PP interval time series were extracted from 10-h Holter ECGs and an automated filter was applied to the RR time series (RRf). Time-domain HRV variables were calculated based on RR, PP, and RRf time series and their relation to the number of AVBs was assessed. Hourly 10- and 60-min segments were extracted to investigate the influence of segment length and recording time on HRV variables. Day-to-day variability and reference intervals of HRV variables were calculated. RESULTS: Variables of short-term HRV were significantly influenced by the number of AVBs when based on RR, but not when based on PP- and RRf time series. PP- and RRf-based HRV variables were in good agreement. The majority of HRV variables were influenced by recording time and ECG segment length. Day-to-day variability of HRV variables was low when based on 10-h ECG recordings but moderate to high when based on 60-min and 10-min recordings. CONCLUSIONS: Second-degree AVBs significantly influence conventional RR-based, but not PP- and RRf-based time-domain HRV variables. However, PP and RRf analyses have limitations and recording length and time of recording must be considered.