Thong Tran, McNames James, Aboy Mateo, Goldstein Brahm
OGI School of Science & Engineering, Oregon Health and Science University, Beaverton, OR 97006, USA.
IEEE Trans Biomed Eng. 2004 Apr;51(4):561-9. doi: 10.1109/TBME.2003.821030.
Currently, no reliable method exists to predict the onset of paroxysmal atrial fibrillation (PAF). We propose a predictor that includes an analysis of the R-R time series. The predictor uses three criteria: the number of premature atrial complexes (PAC) not followed by a regular R-R interval, runs of atrial bigeminy and trigeminy, and the length of any short run of paroxysmal atrial tachycardia. An increase in activity detected by any of these three criteria is an indication of an imminent episode of PAF. Using the Physionet database of the Computers in Cardiology 2001 Challenge, the predictor achieved a sensitivity of 89% and a specificity of 91%.
目前，尚无可靠方法预测阵发性心房颤动（PAF）的发作。我们提出了一种包含R-R时间序列分析的预测器。该预测器采用三个标准：未跟随规则R-R间期的房性早搏（PAC）数量、房性二联律和三联律发作，以及任何短阵阵发性房性心动过速的发作时长。这三个标准中任何一个检测到的活动增加都表明PAF即将发作。利用2001年心脏病学计算机挑战中的Physionet数据库，该预测器的灵敏度达到89%，特异性达到91%。
