Urban R J, Kaiser D L, van Cauter E, Johnson M L, Veldhuis J D
Department of Internal Medicine, University of Virginia School of Medicine, Charlottesville 22908.
Am J Physiol. 1988 Jan;254(1 Pt 1):E113-9. doi: 10.1152/ajpendo.1988.254.1.E113.
The performances of eight currently available computerized pulse-detection algorithms were compared on signal-free noise and physiological luteinizing hormone (LH) time series. Signal-free noise was made to vary from 4 to 36% for Gaussian and empirical distributions. Physiological LH data were obtained by immunoassay of blood samples withdrawn every 5 min for 24 h in 8 healthy men, so that the data sets could be emended to simulate varying sampling intensities. Whenever possible, programs were tested at a presumptive 1% false-positive rate. In relation to signal-free noise, the Santen and Bardin program and its modification manifested elevated false-positive rates when the intraseries coefficients of variation increased. The Regional Dual-Threshold program yielded a 1% false-positive rate except on simulated series with high variance. The Cluster and Detect programs both approximated a 1% false-positive rate and the Ultra program approximated a 2.3% false-positive rate throughout the entire range of variance tested. In regard to physiological LH data, all algorithms disclosed a significant impact of sampling intensity on estimates of LH pulse frequency. Sampling-intensity dependent estimates of LH peak frequency by three of the eight programs (Ultra, Cluster, and Detect) were statistically indistinguishable from each other but distinct from the five other programs tested. Furthermore, when judged in relation to their ability to identify individual peaks, the three congruent programs were minimally distinguishable (McNemar's test). Rather, these programs identified the same particular peaks (as defined by concordance of peak maxima) at least 72% of the time.
在无信号噪声和生理性促黄体生成素(LH)时间序列上,对目前可用的八种计算机化脉冲检测算法的性能进行了比较。对于高斯分布和经验分布,使无信号噪声在4%至36%之间变化。通过对8名健康男性每5分钟采集一次血样,进行24小时免疫测定获得生理性LH数据,以便对数据集进行修正以模拟不同的采样强度。只要有可能,程序都在假定的1%假阳性率下进行测试。关于无信号噪声,当系列内变异系数增加时,Santen和Bardin程序及其修改版本表现出较高的假阳性率。区域双阈值程序除了在高方差模拟系列上外,产生了1%的假阳性率。在整个测试的方差范围内,聚类和检测程序的假阳性率均接近1%,而Ultra程序的假阳性率接近2.3%。关于生理性LH数据,所有算法都揭示了采样强度对LH脉冲频率估计有显著影响。八个程序中的三个(Ultra、聚类和检测)对LH峰值频率的采样强度依赖性估计在统计学上彼此无差异,但与其他五个测试程序不同。此外,当根据它们识别单个峰值的能力进行判断时,这三个一致的程序几乎无法区分(McNemar检验)。相反,这些程序至少72%的时间识别出相同的特定峰值(由峰值最大值的一致性定义)。