Large animals as models of atrial fibrillation

Frydrychowski, Piotr; Michałek, Marcin; Sławuta, Agnieszka; Noszczyk-Nowak, Agnieszka

doi:10.17219/acem/122130

Cited by 6 publications

(1 citation statement)

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“…It is a widely occurring clinical problem in veterinary medicine for which there is a growing interest in developing automated detection methods. Additionally, although other large animals have been used as the models for AF research, 4 , 5 we expect that racing horse models offer significant advantages of subjects being kept in tightly controlled environment, with controlled breeding facilitating genetic analysis. Horses also spontaneously developed AF similar to humans.…”

Section: Introductionmentioning

confidence: 99%

ECG Restitution Analysis and Machine Learning to Detect Paroxysmal Atrial Fibrillation: Insight from the Equine Athlete as a Model for Human Athletes

et al. 2020

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Atrial fibrillation is the most frequent arrhythmia in both equine and human athletes. Currently, this condition is diagnosed via ECG monitoring which lacks sensitivity in about half of cases when it presents in paroxysmal form. We investigated whether the arrhythmogenic substrate present between the episodes of paroxysmal atrial fibrillation (PAF) can be detected using restitution analysis of normal sinus-rhythm ECGs. In this work, ECG recordings were obtained during routine clinical work from control and horses with PAF. The extracted QT, TQ and RR intervals were used for ECG restitution analysis. The restitution data was trained and tested using k-nearest neighbour (k-NN) algorithm with various values of neighbours k to derive a discrimination tool. A combination of QT, RR and TQ intervals was used to analyse the relationship between these intervals and their effects on PAF. A simple majority vote on individual record (one beat) classifications was used to determine the final classification. The k-NN classifiers using two interval measures were able to predict the diagnosis of paroxysmal atrial fibrillation with area under the receiving operating characteristic curve close to 0.8 (RR, TQ with k ≥ 9) and 0.9 (RR, QT with k ≥ 21 or TQ, QT with k ≥ 25). By simultaneously using all three intervals for each beat and a majority vote, mean AUCs of 0.9 were obtained for all tested k values (3 to 41). We concluded that three-dimensional ECG restitution analysis can potentially be used as a metric of an automated method for screening of PAF.

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Section: Introductionmentioning

confidence: 99%