Abstract

In sick sinus syndrome (SSS), pathophysiological abnormalities have been shown not only in the sinus node but also in the atrial muscle, especially of the perinodal portion. To investigate whether the electrophysiological abnormalities of atrial muscle in SSS would induce the characteristic P wavepattern, especially in the initial portion of the P wave, we studied 37 patients with SSS and 67 age-comparable control patients. using the P wave-triggered signal-averaged electrocardiography. Sixteen of 37 SSS patients had paroxysmal atrial fibrillation (Paf). Signal-averaged electrocardiograms were recorded with a band-pass filter of 40–300 Hz and signals of 200 beats or more were averaged with the P wave-triggering technique. The P wave complexes of the three bipolar leads were combined into a spatial magnitude, and then the root mean square voltage for the initial 30 ms (EP30) and the last 20 m (LP20) of filtered P wave were measured. The duration (Ad) and root mean square voltage (RMS) of the total filtered P wave were also measured. SSS with Paf SSS without Pat Control EP30 ( μ V) 2.55 ± 1.17 * 2.16 ± 0.98 * 3.93 ± 1.23 LP20 ( μ V) 1.98 ± 0.40 # † 2.79 ± 1.04 3.35 ± 1.76 Ad (ms) 145.8 ± 16.1 * † 131.2 ± 14.1 $ 123.7 ± 11.7 RMS ( μ V) 6.20 ± 0.41 5.82 ± 0.82 6.20 ± 1.47 * p < 0.0001 # P < 0.005 $ p < 0.05 vs. Control † p < 0.01 vs SSS Without Pat The amplitude of initial portion of filtered P wave was significantly lower and the duration was longer in SSS patients with/without Paf than the controls, while there was no significant difference in the amplitude of the terminal portion between SSS patients without Paf and controls. The criteria of “EP30 ≤ 3.0 μ V and Ad > 130 m” as defining “atrial early potential” gave a sensitivity of 76%, a specificity of 83% and a predictive accuracy of 81% for detection of patients with SSS. These results indicate that the low amplitude signals in the initial portion of filtered P wave were characteristic of SSS, so that the recognition of atrial early potential might be promising to identify patients with SSS.

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