Why the study?
The study investigated the diagnostic properties of the percentage of relative RR interval differences equal to or greater than x% (pRRx%) to distinguish atrial fibrillation from sinus rhythm.
Does the relative heart rate variability parameter pRR3.25% improve the diagnostic detection of atrial fibrillation compared to other parameters in 1-min ECG segments?
Observational (n=64,910)
Does the relative heart rate variability parameter pRR3.25% improve the diagnostic detection of atrial fibrillation compared to other parameters in 1-min ECG segments?
Answers are grounded in this paper and cite their sources.
The pRR3.25% parameter offers excellent and computationally simple diagnostic properties for detecting atrial fibrillation in short ECG segments, making it highly applicable for wearable technologies.
BACKGROUND: The ratio of the difference between neighboring RR intervals to the length of the preceding RR interval (x%) represents the relative change in the duration between two cardiac cycles. We investigated the diagnostic properties of the percentage of relative RR interval differences equal to or greater than x% (pRRx%) with x% in a range between 0.25% and 25% for the distinction of atrial fibrillation (AF) from sinus rhythm (SR). METHODS: We used 1-min ECG segments with RR intervals with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). The properties of pRRx% for different x% were analyzed using the statistical procedures and metrics commonly used to characterize diagnostic methods. RESULTS: The distributions of pRRx% for AF and SR differ significantly over the whole studied range of x% from 0.25% to 25%, with particularly outstanding diagnostic properties for the x% range of 1.5% to 6%. However, pRR3.25% outperformed other pRRx%. Firstly, it had one of the highest and closest to perfect areas under the curve (0.971). For pRR3.25%, the optimal threshold for distinction AF from SR was set at 75.32%. Then, the accuracy was 95.44%, sensitivity was 97.16%, specificity was 93.76%, the positive predictive value was 93.85%, the negative predictive value was 97.11%, and the diagnostic odds ratio was 514. The excellent diagnostic properties of pRR3.25% were confirmed in the publicly available MIT-BIH Atrial Fibrillation Database. In a direct comparison, pRR3.25% outperformed the diagnostic properties of pRR31 (the percentage of successive RR intervals differing by at least 31 ms), i.e., so far, the best single parameter differentiating AF from SR. CONCLUSIONS: A family of pRRx% parameters has excellent diagnostic properties for AF detection in a range of x% between 1.5% and 6%. However, pRR3.25% outperforms other pRRx% parameters and pRR31 (until now, probably the most robust single heart rate variability parameter for AF diagnosis). The exquisite pRRx% diagnostic properties for AF and its simple computation make it well-suited for AF detection in modern ECG technologies (mobile/wearable devices, biopatches) in long-term monitoring. The diagnostic properties of pRRx% deserve further exploration in other databases with AF.
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Buś et al. (2023) conducted an observational in Atrial Fibrillation (n=64,910). pRR3.25% (percentage of relative RR interval differences equal to or greater than 3.25%) vs. Other pRRx% parameters and pRR31 was evaluated on Accuracy for the distinction of atrial fibrillation from sinus rhythm.
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