Bollmann Andreas, Husser Daniela, Stridh Martin, Soernmo Leif, Majic Monica, Klein Helmut U, Olsson S Bertil
Department of Cardiology, University Hospital Magdeburg, Magdeburg, Germany.
J Cardiovasc Electrophysiol. 2003 Oct;14(10 Suppl):S154-61. doi: 10.1046/j.1540.8167.90305.x.
Frequency analysis of fibrillation (FAF) and time-frequency analysis (TFA) were developed recently in order to quantify atrial electrical remodeling in atrial fibrillation (AF) from the surface ECG. This article describes the experience with these two different frequency analysis techniques in consecutive AF patients and discusses possible applications in AF research and clinical decision-making.
Baseline 2-minute, high-gain, high-resolution ECG recordings using three bipolar leads were obtained from 80 consecutive patients with AF lasting > 24 hours. A power spectrum was obtained using Fourier analysis following spatiotemporal QRST cancellation. The dominant fibrillatory rate (in fibrillations per minute [fpm]) was derived (FAF). Stability of the instantaneous fibrillatory rate measured in overlapping 1-second segments was expressed as the segment proportion with consecutive rate differences < 6 fpm (TFA). An adequate power spectrum that could be submitted for determination of fibrillatory rate was obtained in all patients. Dominant atrial rates ranged between 288 and 534 fpm and showed a high correlation (R = 0. 878-0.911, P < 0.001) when assessed from the three different leads. The average instantaneous fibrillatory rate was inversely related with its stability (R = -0.417, P < 0.001). It was closely related with the dominant fibrillatory rate obtained from FAF (R = 0.948, P < 0.001). A literature review revealed that pharmacologic or electrical cardioversion and AF pace termination success rates were highly dependent on fibrillatory rate.
Atrial fibrillatory rate and its variability can be reliable obtained from the surface ECG in AF patients. These parameters exhibit a significant interindividual variability allowing individual quantification of the atrial electrical remodeling process and might prove useful for predicting therapy efficacy.
为了从体表心电图量化心房颤动（AF）时的心房电重构，近期开发了颤动频率分析（FAF）和时频分析（TFA）。本文描述了在连续的AF患者中应用这两种不同频率分析技术的经验，并讨论了它们在AF研究和临床决策中的可能应用。
对80例持续时间>24小时的连续AF患者，使用三根双极导联获取2分钟的基线高增益、高分辨率心电图记录。在进行时空QRST消除后，采用傅里叶分析获得功率谱。得出主导颤动率（以每分钟颤动次数[fpm]表示）（FAF）。在重叠的1秒时间段内测量的瞬时颤动率稳定性表示为连续率差<6 fpm的时间段比例（TFA）。所有患者均获得了可用于确定颤动率的合适功率谱。主导心房率在288至534 fpm之间，从三根不同导联评估时显示出高度相关性（R = 0.878 - 0.911，P < 0.001）。平均瞬时颤动率与其稳定性呈负相关（R = -0.417，P < 0.001）。它与通过FAF获得的主导颤动率密切相关（R = 0.948，P < 0.001）。文献综述表明，药物或电复律以及AF起搏终止成功率高度依赖于颤动率。
AF患者的心房颤动率及其变异性可从体表心电图可靠获得。这些参数表现出显著的个体间变异性，允许对心房电重构过程进行个体量化，可能对预测治疗效果有用。
