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

Abstract

equine athletes have a pattern of exercise which is analogous to human athletes and the cardiovascular risks in both species are similar. Both species have a propensity for atrial fibrillation (AF), which is challenging to detect by ECG analysis when in paroxysmal form. We hypothesised that the proarrhythmic background present between fibrillation episodes in paroxysmal AF (PAF) might be detectable by complexity analysis of apparently normal sinus-rhythm ECGs. In this retrospective study ECG recordings were obtained during routine clinical work from 82 healthy horses and from 10 horses with a diagnosis of PAF. Artefact-free 60-second strips of normal sinus-rhythm ECGs were converted to binary strings using threshold crossing, beat detection and a novel feature detection parsing algorithm. Complexity of the resulting binary strings was calculated using Lempel-Ziv ('76 & '78) and Titchener complexity estimators. Dependence of Lempel-Ziv '76 and Titchener T-complexity on the heart rate in ECG strips obtained at low heart rates (25-60 bpm) and processed by the feature detection method was found to be significantly different in control animals and those diagnosed with PAF. This allows identification of horses with PAF from sinus-rhythm ECGs with high accuracy.www.nature.com/scientificreports www.nature.com/scientificreports/ Complexity analysis. Estimation of the binary string complexities was facilitated by a custom implementation of a complexity evaluator developed in C++ for the Linux operating system. The program simultaneously performs complexity analysis using three previously published methods: Lempel-Ziv '76 24 , Lempel-Ziv '78 28 and Titchener T-complexity 31 . All three methods estimate the complexity of a symbolic string by identifying the number of sub-strings (factors) needed to build it by a computer capable of a certain limited set of operations. These methods differ by the algorithms of decomposition of the source strings to sub-strings and therefore produce different estimates for the same source data (Fig. 5). The detailed description of these methods may be found in the corresponding publications. To eliminate the dependency of complexity values on the length of the source string (n), Lempel-Ziv '76 (abbreviated as LZ76) complexity values were normalised to the n/log 2 (n) value 25 . Lempel-Ziv '78 (abbreviated as LZ78) values were normalised to sequence length. For T-complexity, average entropy values were used.Statistical analyses. Parametric data are expressed as mean ± standard deviation of mean. Statistical analyses and plotting were done using GNU R 40 . An unpaired two-sided t-test (using Welch's correction for unequal variances) was used for two-group comparisons and ANOVA test with Tukey correction for multiple comparisons of groups, with significance between data sets accepted at p < 0.05.

Implantable loop recorders can detect paroxysmal atrial fibrillation in Standardbred racehorses with intermittent poor performance

“…Due to the short‐lasting and unpredictable nature of PAF it is difficult to diagnose as it would require long‐term Holter ECG recordings. In the past, efforts have been made to overcome this and recently, a new computerised complexity analysis of apparently normal SR ECGs were able to identify PAF horses 4 . Also, handhold ECG devices are now available, making direct detection possible 5 .…”

“…In the past, efforts have been made to overcome this and recently, a new computerised complexity analysis of apparently normal SR ECGs were able to identify PAF horses. 4 Also, handhold ECG devices are now available, making direct detection possible. 5 Early recognition of AF is essential as long lasting AF becomes more resistant to treatment.…”

Prediction of Paroxysmal Atrial Fibrillation From Complexity Analysis of the Sinus Rhythm ECG: A Retrospective Case/Control Pilot Study

“…An alternative refinement may be to determine if multiple-lead ECGs or alternative complexity estimates are better, but this remains to be explored. Other strategies might be derived to process higher quality recordings, for example, using more complex ECG parsing techniques but simpler analysis methods (Alexeenko et al, 2020). The method also required a cardiologist to scrutinize ECG traces before analysis to exclude abnormalities, and although they are relatively uncommon in a general population (Sirichand et al, 2017) a fully automated process would need some preliminary screening process (see Limitations, below).…”

Fundamentals of arrhythmogenic mechanisms and treatment strategies for equine atrial fibrillation

“…The amount of data available on AF pathophysiology in the horse is unfortunately limited and it is not clear whether equine AF involves hierarchical or anarchical mechanisms or whether both mechanisms are likely. Techniques such as intracardiac mapping 61–63 and computer‐based ECG analysis 20,64–66 are in their infancy for horses and hopefully should improve our understanding of this complex rhythm disturbance. Imaging techniques 67–69 and molecular biological data 15–17 are still limited, but a lot can be learned from studies in animal models and human patients 21,28 …”