Sleep-related Obstructive Sleep Apnea Research Articles

Dynamic changes in nocturnal blood glucose levels are associated with sleep-related features in patients with obstructive sleep apnea

Obstructive sleep apnea (OSA) has a bidirectional relationship with insulin resistance conditions; however, the mechanism remains unclear. This study aimed to compare dynamic nocturnal glucose changes among patients with OSA of varying levels of severity and evaluate temporal changes associated with the cardinal features of OSA (sympathetic hyperactivation, intermittent hypoxemia, and sleep fragmentation) in nondiabetic subjects. Nocturnal glucose was measured with a continuous glucose monitoring device every 5 min during polysomnography (PSG). The OSA features were evaluated using heart rate variability (HRV), minimum saturation, and electroencephalography. Eleven subjects with moderate to severe OSA and 12 subjects with no or mild OSA were evaluated. Those with moderate to severe OSA showed an increasing trend in blood glucose levels after sleep onset, whereas those without or with mild OSA showed a decreasing trend (F = 8.933, p < 0.001). Delta band power also showed different trends during sleep between the two groups (F = 2.991, p = 0.009), and minimum saturation remained lower in the moderate to severe OSA group than in the no or mild OSA group. High degrees of coupling between nocturnal glucose levels and each OSA feature were observed. Altered trends in nocturnal glucose in moderate to severe OSA may reflect glucose intolerance and result in metabolic consequences. Managing the features of sleep-related OSA may have implications for metabolic management in the future.

The association of body mass index values with severity and phenotype of sleep-disordered breathing.

To investigate the relationship between body mass index (BMI) and the severity of obstructive sleep apnea (OSA) and to determine the BMI cut-off values for sleep-disordered breathing among adult population. Data from 515 patients were evaluated retrospectively. These included demographic data, BMI, apnea-hypopnea index (AHI), oxygen saturation (SaO2) and oxygen desaturation index (ODI). The BMI cutoff value for sleep-disordered breathing was determined and comparisons were made between two groups of patients (BMI ≤ 33 and BMI > 33). Descriptive and comparative analyses were performed using SPSS, version 24. Higher BMI values were found to be correlated with diagnosis and severity of OSA and reduced sleep efficiency. Patients in the BMI > 33 group had significantly higher rates of co-morbid diseases than patients in the BMI ≤ 33 group. Patients with BMI ≤ 33 had significantly lower ODI values than patients with BMI > 33. In patients with BMI > 33, arousal index was significantly higher and SaO2 values were lower than those with BMI ≤ 33. In rapid eye movement (REM) sleep-related OSA, BMI values were higher than positional/classical OSA. Patients with higher BMI experienced frequent nocturnal oxygen desaturation periods resulting in higher arousal indexes and decreased sleep efficiency. REM sleep-related OSA and high BMI values together may lead to increased nocturnal oxygen demand. We recommend the threshold values of BMI > 33 to be considered for screening OSA among adult population.

Sleeping Together: A Pilot Study of the Effects of Shared Sleeping on Adherence to CPAP Treatment in Obstructive Sleep Apnea

To examine the sleep of married couples, recorded together in the laboratory before and after the husband is treated with continuous positive airway pressure (CPAP) to control his obstructive sleep apnea (OSA). The purpose was to investigate how these data relate to shared sleeping when he is on CPAP and his adherence to this treatment. Following a split-night diagnosis of OSA with CPAP titration, 10 married men slept for 2 additional nights with their non-apneic wife while both were recorded. The first night included a standard baseline 12-channel clinical polysomnogram without treatment. Following 2 weeks of home CPAP, the couple returned for a second polysomnography night with the husband on CPAP. Both partners completed Epworth Sleepiness Scales and Sleep Apnea Quality of Life Interviews each lab night. During the intervening 2 weeks, sleep logs were completed daily noting if CPAP was used, the presence of snoring, and where and how well they slept. Adherence data from machine downloads were obtained after an average of 4.6 months. The husbands' baseline sleep differed significantly from their wives on 6 of 7 sleep variables related to OSA and on Epworth Sleepiness Scale scores. Their sleep did not differ the second night, except for his lower percentage of slow wave sleep. Adherence to CPAP was unrelated to OSA severity but positively related to the number of nights the couple slept together during the 2 weeks of home CPAP. The frequency of sleeping together was negatively related to the wives' arousal frequency on laboratory nights. Although CPAP controls a husband's sleep-related OSA symptoms, his treatment adherence is strongly related to his wife sharing the bed. Addressing the wife's sensitivity to arousals when bed sharing may improve the husband's treatment adherence.