Herzog Michael, Schmidt Andreas, Bremert Thomas, Herzog Beatrice, Hosemann Werner, Kaftan Holger
Department of Oto-Rhino-Laryngology, Head and Neck Surgery, Ernst-Moritz-Arndt University, Walther-Rathenau-Street 43-45, 17487, Greifswald, Germany.
Eur Arch Otorhinolaryngol. 2008 Jan;265(1):105-13. doi: 10.1007/s00405-007-0408-8. Epub 2007 Aug 7.
Snoring occurs as a major symptom in patients with sleep disordered breathing (SDB). The aetiology of snoring remains still unclear despite various attempts to localize snoring. The correlation between different snoring sounds and the severity of SDB has not yet been investigated in a larger population. The aim of this study was to record and analyse snoring sounds and to correlate the obtained data with clinical and polysomnographical parameters. Sixty male patients with suspected SDB and reported snoring underwent a clinical examination and night time polysomnography. The parallel digitally recorded snoring sounds were analysed by fast fourier transformation (FFT). Peak intensity was determined from the power spectrum. The periodicity of snoring was classified into rhythmic and non-rhythmic snoring according to the presence of air flow interruptions due to obstructive apneas. Patients with primary snoring revealed peak intensities between 100 and 300 Hz. Patients with an obstructive sleep apnea syndrome (OSAS) revealed peak intensities above 1,000 Hz. Polysomnographical data (AHI, mean and minimum SpO(2)) as well as body mass index (BMI) correlated with peak intensity of the power spectrum. None of the parameters of the clinical examination correlated with peak intensity. Frequency analysis of snoring sounds provides a useful diagnostic tool to distinguish between different patterns of snoring and respective SDB. The topodiagnosis of snoring is not possible by means of frequency analysis or clinical examination alone. Acoustical analysis of snoring sounds seems a promising additional diagnostic tool to verify different types of SDB in snoring patients.
打鼾是睡眠呼吸障碍(SDB)患者的主要症状。尽管人们进行了各种尝试来确定打鼾的部位,但其病因仍不明确。在更大规模的人群中,尚未对不同鼾声与SDB严重程度之间的相关性进行研究。本研究的目的是记录和分析鼾声,并将所得数据与临床和多导睡眠图参数相关联。60名怀疑患有SDB且有打鼾报告的男性患者接受了临床检查和夜间多导睡眠监测。通过快速傅里叶变换(FFT)对同步数字记录的鼾声进行分析。从功率谱中确定峰值强度。根据由于阻塞性呼吸暂停导致的气流中断情况,将打鼾的周期性分为有节律性打鼾和无节律性打鼾。原发性打鼾患者的峰值强度在100至300赫兹之间。阻塞性睡眠呼吸暂停综合征(OSAS)患者的峰值强度高于1000赫兹。多导睡眠图数据(呼吸暂停低通气指数、平均和最低血氧饱和度)以及体重指数(BMI)与功率谱的峰值强度相关。临床检查的各项参数均与峰值强度无关。鼾声的频率分析为区分不同类型的打鼾和相应的SDB提供了一种有用的诊断工具。仅通过频率分析或临床检查无法进行打鼾的定位诊断。鼾声的声学分析似乎是一种有前景的辅助诊断工具,可用于验证打鼾患者不同类型的SDB。