IEEE Trans Biomed Eng. 2024 Jan;71(1):106-113. doi: 10.1109/TBME.2023.3293252. Epub 2023 Dec 22.
The episode patterns of paroxysmal atrial fibrillation (AF) may carry important information on disease progression and complication risk. However, existing studies offer very little insight into to what extent a quantitative characterization of AF patterns can be trusted given the errors in AF detection and various types of shutdown, i.e., poor signal quality and non-wear. This study explores the performance of AF pattern characterizing parameters in the presence of such errors.
To evaluate the performance of the parameters AF aggregation and AF density, both previously proposed to characterize AF patterns, the two measures mean normalized difference and the intraclass correlation coefficient are used to describe agreement and reliability, respectively. The parameters are studied on two PhysioNet databases with annotated AF episodes, also accounting for shutdowns due to poor signal quality.
The agreement is similar for both parameters when computed for detector-based and annotated patterns, which is 0.80 for AF aggregation and 0.85 for AF density. On the other hand, the reliability differs substantially, with 0.96 for AF aggregation but only 0.29 for AF density. This finding suggests that AF aggregation is considerably less sensitive to detection errors. The results from comparing three strategies to handle shutdowns vary considerably, with the strategy that disregards the shutdown from the annotated pattern showing the best agreement and reliability.
Due to its better robustness to detection errors, AF aggregation should be preferred. To further improve performance, future research should put more emphasis on AF pattern characterization.
阵发性心房颤动（AF）的发作模式可能携带与疾病进展和并发症风险相关的重要信息。然而，现有的研究几乎没有深入探讨在 AF 检测和各种类型的停机（即信号质量差和不佩戴）导致的误差下，对 AF 模式进行定量描述的可信度。本研究探讨了在存在这些误差的情况下，AF 模式特征参数的性能。
为了评估先前提出的用于描述 AF 模式的两个参数，即 AF 聚集和 AF 密度的性能，使用平均归一化差和组内相关系数这两个指标分别描述一致性和可靠性。研究参数时，同时考虑了由于信号质量差而导致的停机情况，使用了两个带有注释的 AF 发作的 PhysioNet 数据库。
当根据基于检测器的模式和注释模式计算时，两个参数的一致性相似，AF 聚集的一致性为 0.80，AF 密度的一致性为 0.85。另一方面，可靠性差异很大，AF 聚集的可靠性为 0.96，而 AF 密度的可靠性仅为 0.29。这一发现表明，AF 聚集对检测误差的敏感度较低。比较三种处理停机策略的结果差异很大，忽略注释模式中的停机的策略显示出最佳的一致性和可靠性。
由于其对检测误差具有更好的鲁棒性，因此应优先选择 AF 聚集。为了进一步提高性能，未来的研究应更加重视 AF 模式的特征描述。
