Heart rate variability parameters in horses distinguish atrial fibrillation from sinus rhythm before and after successful electrical cardioversion

Abstract

BACKGROUND: Atrial fibrillation (AF) is the most common pathological arrhythmia in horses. After successful treatment, recurrence is common. Heart rate monitors are easily applicable in horses and some devices offer basic heart rate variability (HRV) calculations. If HRV can be used to distinguish between AF and sinus rhythm (SR), this could become a monitoring tool for horses at risk for recurrence of AF. OBJECTIVES: The purpose of this study was to assess whether in horses AF (before cardioversion) and SR (after cardioversion) can be differentiated based upon HRV parameters. STUDY DESIGN: Cohort study with internal controls. METHODS: Six HRV parameters were determined in 20 horses, both in AF and in SR, at rest (2-and 5-min and 1-and 4-h recordings) and during exercise (walk and trot, 2-min recordings). Time-domain (standard deviation of the NN intervals, root mean squared successive differences in NN intervals and triangular index), frequency domain (low/high frequency ratio) and nonlinear parameters (standard deviation of the Poincaré plot [SD]1 and SD2) were used. Statistical analysis was done using paired Wilcoxon signed rank tests and receiver operating characteristic curves. RESULTS: HRV was higher during AF compared to SR. Results for the detection of AF were good (area under the receiver operating characteristic curve [AUC] 0.8-1) for most HRV parameters. Root mean squared successive differences in NN intervals and SD1 yielded the best results (AUC 0.9-1). Sensitivity and specificity were high for all parameters at all recordings, but highest during exercise. Although AUCs improved with longer recordings, short recordings were also good (AUC 0.8-1) for the detection of AF. In horses with frequent second degree atrioventricular block, HRV at rest is increased and recordings at walk or trot are recommended. MAIN LIMITATIONS: Animals served as their own controls and there was no long-term follow-up to identify AF recurrence. CONCLUSIONS: AF (before cardioversion) and SR (after cardioversion) could be distinguished with HRV. This technique has promise as a monitoring tool in horses at risk for AF development. Accepted ArticleThis article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/evj.12684 This article is protected by copyright. All rights reserved.

The complexity of clinically-normal sinus-rhythm ECGs is decreased in equine athletes with a diagnosis of paroxysmal atrial fibrillation

“…This tool produced a highly accurate automated discriminator between PAF and controls using sinus-rhythm ECGs (AUC exceeding 0.9 for both complexity estimators). A key advantage of the proposed method is that, unlike manual ECG analysis or other automated methods of AF detection based on estimation of signal stochasticity 32 , it does not require the actual fibrillation episode to occur during the ECG recording. However, this also means that such a technique does not actually document the episode of AF as an ultimate proof required for the diagnosis to be confirmed.…”

The use of heart rate variability analysis to detect arrhythmias in horses undergoing a standard treadmill exercise test

“…Although a recent equine study highlighted the somewhat unconventional use of HRV analyses to aid in identification of AF. In their study, HRV analyses (particularly RMSSD) were used as a way to differentiate NSR from AF in horses at rest and during lunging exercise …”

Can heart rate variability parameters derived by a heart rate monitor differentiate between atrial fibrillation and sinus rhythm?

“…Three different systems of heart rate detection (electrodes + RR detection) were compared. A modified base apex ECG was recorded as described elsewhere [ 20 ], using adhesive electrodes (Skintact, Leonhard Lang GmbH, Innsbruck, Austria) and analyzed using a commercial ECG software program (Televet 100 software version 5.1.2, Engel Engineering Services GmbH, Heusenstamm, Germany) with a detection limit of 8%, meaning that all RR intervals differing more than 8% from the previous RR interval were detected as outliers, but included in the analysis. First, the RR intervals automatically detected by the ECG software, leaving errors in QRS detection in place, were exported (ECG Aut ).…”

“…Since arrhythmia, especially AF, leads to an increased beat-to-beat interval variation, HRV parameters describing short-term variability are increased compared to sinus rhythm (SR) and algorithms using HRV parameters are implemented in devices detecting AF in humans [ 15 – 19 ]. In horses, HRV has already been evaluated for the detection of AF in horses before and after transvenous electrical cardioversion [ 20 ]. In that study, 6 different HRV variables were calculated from RR intervals after beat-to-beat QRS identification on the ECG trace, both during AF and during SR. RMSSD, the root mean squared successive differences in RR interval, yielded the best results with high sensitivity and specificity to distinguish AF from SR.…”