• Sleep Medicine and Psychophysiology
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• v.9 no.1
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• pp.34-40
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• 2002

Objectives: The gold standard for diagnosing obstructive sleep apnea syndrome (OSAS) is nocturnal polysomnography (NPSG). This is rather expensive and somewhat inconvenient, however, and consequently simpler and cheaper alternatives to NPSG have been proposed. Oximetry is appealing because of its widespread availability and ease of application. In this study, we have evaluated whether oximetry alone can be used to diagnose or screen OSAS. The diagnostic performance of an analysis algorithm using arterial oxygen saturation ($SaO_2$) base on 'dip index', mean of $SaO_2$, and CT90 (the percentage of time spent at $SaO_2$<90%) was compared with that of NPSG. Methods: Fifty-six patients referred for NPSG to the Division of Sleep Studies at Seoul National University Hospital, were randomly selected. For each patient, NPSG with oximetry was carried out. We obtained three variables from the oximetry data such as the dip index most linearly correlated with respiratory disturbance index (RDI) from NPSG, mean $SaO_2$, and CT90 with diagnosis from NPSG. In each case, sensitivity, specificity and positive and negative predictive values of oximetry data were calculated. Results: Thirty-nine patients out of fifty-six patients were diagnosed as OSAS with NPSG. Mean RDI was 17.5, mean $SaO_2$ was 94.9%, and mean CT90 was 5.1%. The dip index [4%-4sec] was most linearly correlated with RDI (r=0.861). With dip index [4%-4sec]${\geq}2$ as diagnostic criteria, we obtained sensitivity of 0.95, specificity of 0.71, positive predictive value of 0.88, and negative predictive value of 0.86. Using mean $SaO_2{\leq}97%$, we obtained sensitivity of 0.95, specificity of 0.41, positive predictive value of 0.79, and negative predictive value of 0.78. Using $CT90{\geq}5%$, we obtained sensitivity of 0.28, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of 0.38. Conclusions: The dip index [4%-4sec] and mean $SaO_2{\leq}97%$ obtained from nocturnal oximetry data are helpful in diagnosis of OSAS. CT90${\leq}$5% can be also used in excluding OSAS.

• Sleep Medicine and Psychophysiology
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• v.24 no.2
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• pp.106-117
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• 2017

Objectives: Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that is characterized by repetitive collapse or partial collapse of the upper airway during sleep in spite of ongoing effort to breathe. It is believed that OSA is usually worsened in REM sleep, because muscle tone is suppressed during REM sleep. However, many cases showed a higher apnea-hypopnea index (AHI) during NREM sleep than during REM sleep. We aimed here to determine the characteristics of REM sleep-dependent OSA (REM-OSA) and NREM sleep-dependent OSA (NREM-OSA). Methods: Five hundred sixty polysomnographically confirmed adult OSA subjects were studied retrospectively. All patients were classified into 3 groups based on the ratio between REM-AHI and NREM-AHI. REM-OSA was defined as REM-AHI/NREM-AHI > 2, NREM-OSA as NREM-AHI/REM-AHI > 2, and the rest as sleep stage-independent OSA (IND-OSA). In addition to polysomnography, questionnaires related to subjective sleep quality, daytime sleepiness, and emotion were completed. Chi-square test, ANOVA, and ANCOVA were performed. Results: There was no age difference among subgroups. The REM-OSA group was comprised of large proportions of mild OSA and female OSA patients. These patients experienced poor sleep and more negative emotions than other two groups. The AHI and oxygen desaturation index (ODI) were lowest in REM-OSA. Sleep efficiency and N3 percentage of REM-OSA were higher than in NREM-OSA. The percentage of patients who slept in a supine position was higher in REM-OSA than other subgroups. IND-OSA showed higher BMI and larger neck circumference and abdominal circumference than REM-OSA. The patients with IND-OSA experienced more sleepiness than the other groups. AHI and ODI were highest in IND-OSA. NREM-OSA presented the shortest total sleep time and the lowest sleep efficiency. NREM-OSA showed shorter sleep latency and REM latency and higher percentage of N1 than those of REM-OSA and the highest proportion of those who slept in a lateral position than other subgroups. NREM-OSA revealed the highest composite score on the Horne and ${\ddot{O}}stberg$ questionnaire. With increased AHI severity, the numbers of apnea and hypopnea events during REM sleep decreased, and the numbers of apnea and hypopnea events during NREM sleep increased. The results of ANCOVA after controlling age, sex, BMI, NC, AC, and AHI showed the lowest sleep efficiency, the highest AHI in the supine position, and the highest percentage of waking after sleep onset in NREM-OSA. Conclusion: REM-OSA was associated with the mild form of OSA, female sex, and negative emotions. IND-OSA was associated with the severe form of OSA. NREM-OSA was most closely related to position and showed the lowest sleep efficiency. Sleep stage-dependent characteristics could provide better understanding of OSA.