STUDY OBJECTIVES: To evaluate the validity of a novel method of using tracheal sound analysis for the diagnosis of sleep apnea-hypopnea syndrome. DESIGN: Retrospective analysis in consecutive patients. SETTING: A sleep clinic in a general hospital. PATIENTS: A total of 383 patients who were referred for suspected sleep apnea-hypopnea syndrome and underwent diagnostic polysomnography with sufficient quality. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Ordinary polysomnography with simultaneous tracheal sound recording was performed. The apnea-hypopnea index (AHI) was calculated as the number of apnea and hypopnea events per hour of sleep. Tracheal sounds were digitized and recorded as power spectra. An automated computer program detected transient falls (TS-dip) in the time series of moving average of the logarithmic power of tracheal sound. We defined the tracheal sound-respiratory disturbance index (TS-RDI) as the number of TS-dips per hour of examination. We also calculated the oxygen desaturation index (the number of SaO2 dips of at least 4% per hour of examination). The TS-RDI highly correlated with AHI (r = 0.93). The mean (+/- SD) difference between the TS-RDI and AHI was -8.4 +/- 10.4. The diagnostic sensitivity and specificity of the TS-RDI when the same cutoff value was used as for AHI were 93% and 67% for the AHI cutoff value of 5 and 79% and 95% for the AHI cutoff value of 15. The agreement between the TS-RDI and AHI was better than that between the oxygen desaturation index and AHI. CONCLUSIONS: The fully automated tracheal sound analysis demonstrated a relatively high performance in the diagnosis of sleep apnea-hypopnea syndrome. We think that this method is useful for the portable monitoring of sleep apnea-hypopnea syndrome.
STUDY OBJECTIVES: To evaluate the validity of a novel method of using tracheal sound analysis for the diagnosis of sleep apnea-hypopnea syndrome. DESIGN: Retrospective analysis in consecutive patients. SETTING: A sleep clinic in a general hospital. PATIENTS: A total of 383 patients who were referred for suspected sleep apnea-hypopnea syndrome and underwent diagnostic polysomnography with sufficient quality. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Ordinary polysomnography with simultaneous tracheal sound recording was performed. The apnea-hypopnea index (AHI) was calculated as the number of apnea and hypopnea events per hour of sleep. Tracheal sounds were digitized and recorded as power spectra. An automated computer program detected transient falls (TS-dip) in the time series of moving average of the logarithmic power of tracheal sound. We defined the tracheal sound-respiratory disturbance index (TS-RDI) as the number of TS-dips per hour of examination. We also calculated the oxygen desaturation index (the number of SaO2 dips of at least 4% per hour of examination). The TS-RDI highly correlated with AHI (r = 0.93). The mean (+/- SD) difference between the TS-RDI and AHI was -8.4 +/- 10.4. The diagnostic sensitivity and specificity of the TS-RDI when the same cutoff value was used as for AHI were 93% and 67% for the AHI cutoff value of 5 and 79% and 95% for the AHI cutoff value of 15. The agreement between the TS-RDI and AHI was better than that between the oxygen desaturation index and AHI. CONCLUSIONS: The fully automated tracheal sound analysis demonstrated a relatively high performance in the diagnosis of sleep apnea-hypopnea syndrome. We think that this method is useful for the portable monitoring of sleep apnea-hypopnea syndrome.
Authors: Mark B Norman; Sally Middleton; Odette Erskine; Peter G Middleton; John R Wheatley; Colin E Sullivan Journal: Sleep Date: 2014-09-01 Impact factor: 5.849
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Authors: Christoph Kalkbrenner; Manuel Eichenlaub; Stefan Rüdiger; Cornelia Kropf-Sanchen; Wolfgang Rottbauer; Rainer Brucher Journal: Med Biol Eng Comput Date: 2017-08-29 Impact factor: 2.602
Authors: A Kulkas; E Rauhala; E Huupponen; J Virkkala; M Tenhunen; A Saastamoinen; S-L Himanen Journal: Med Biol Eng Comput Date: 2008-02-21 Impact factor: 2.602
Authors: Christoph Kalkbrenner; Manuel Eichenlaub; Stefan Rüdiger; Cornelia Kropf-Sanchen; Rainer Brucher; Wolfgang Rottbauer Journal: J Clin Sleep Med Date: 2017-10-15 Impact factor: 4.062