Paul V E, O'Nunain S, Malik M, Camm A J
Department of Cardiological Sciences, St. Georges Hospital Medical School, London, United Kingdom.
Pacing Clin Electrophysiol. 1990 Dec;13(12 Pt 2):1943-7. doi: 10.1111/j.1540-8159.1990.tb06921.x.
The automatic discrimination of physiological from pathological tachycardias by rate criteria alone lacks adequate specificity. Tachycardia detection algorithms based upon morphological analysis of the endocardial electrogram have been attributed high specificity although their specificity has not been proven. A previous study had shown temporal electrogram analysis (TEA) to be an algorithm of high sensitivity in the detection of ventricular arrhythmias despite low computational demands. In this study, the specificity and potential for automatic implementation have been assessed. Manual adjustment of thresholds for individual patients gave a maximum potential sensitivity of 97% (26/27 arrhythmias correctly recognized as non-sinus). The use of automatic setting of thresholds reduced sensitivity to 81%. The specificity of the algorithm, as assessed by exercise testing, was only 60%.
仅通过心率标准自动区分生理性与病理性心动过速缺乏足够的特异性。基于心内膜电图形态分析的心动过速检测算法虽被认为具有高特异性，但其特异性尚未得到证实。先前的一项研究表明，尽管计算要求较低，但时间电图分析（TEA）在检测室性心律失常方面是一种高灵敏度的算法。在本研究中，对其特异性和自动实施的潜力进行了评估。对个体患者手动调整阈值可使最大潜在灵敏度达到97%（27例心律失常中有26例被正确识别为非窦性）。使用自动设置阈值会使灵敏度降至81%。通过运动试验评估，该算法的特异性仅为60%。
