Faculty Bibliography

RATIONALE/BACKGROUND:Home sleep apnea testing (HSAT) typically does not include electroencephalogram (EEG) monitoring for sleep assessment. In patients with insomnia and low sleep efficiency, overestimation of the sleep period can result from absence of EEG, which will reduce sleep disordered breathing (SDB) indices and may lead to a false-negative result. OBJECTIVE:To validate a single channel frontal EEG for scoring sleep versus wake against full EEG during polysomnography, and then to examine the utility of adding this single channel EEG to standard HSAT to prevent false-negative results. METHODS:), to calculate AHI4 and RDI and the effect on OSA diagnosis and severity. Analyses were repeated in 69 patients with poor sleep suggesting insomnia plus Epworth Sleepiness Scale < 7 as well as in 38 patients ultimately shown to have sleep efficiency < 70% on HSAT with EEG. MEASUREMENTS AND MAIN RESULTS/RESULTS:Single channel and full EEG during polysomnography agreed on sleep versus wake in 92-95% of all epochs. HSAT without EEG overestimated the sleep period by 20% (VST = 440 ± 76 min vs TST = 356 ± 82 min), had a false-negative rate of 8% by AHI4 criteria, and underestimated disease severity in 11% of all patients. Sub-group analysis of patients with subjective poor sleep suggesting insomnia did not change the results. Patients later shown to have low sleep efficiency had lower SDB indices and a 20.8% false negative rate of sleep apnea diagnosis. CONCLUSIONS:were moderate, suggesting utility for ruling out OSA, there was a specific subgroup in whom there were significant missed diagnoses. However, we were unable to identify this subgroup a priori.

RATIONALE: Recent evidence suggests that Obstructive Sleep Apnea (OSA) may be a risk factor for developing Mild Cognitive Impairment and Alzheimer's disease. However, how sleep apnea affects longitudinal risk for Alzheimer's disease is less well understood. OBJECTIVE: To test the hypothesis that there is an association between severity of OSA and longitudinal increase in amyloid burden in cognitively normal elderly. METHODS: Data was derived from a 2-year prospective longitudinal study that sampled community-dwelling healthy cognitively normal elderly. Subjects were healthy volunteers between the ages of 55 to 90, were non-depressed and had a consensus clinical diagnosis of cognitively normal. CSF Amyloid beta was measured using ELISA. Subjects received Pittsburgh compound B Positron Emission Tomography scans following standardized procedures. Monitoring of OSA was completed using a home sleep recording device. MEASUREMENTS AND MAIN RESULTS: We found that severity of OSA indices (lnAHIall [F1,88=4.26, p<.05] and lnAHI4% [F1,87=4.36, p<.05]) were associated with annual rate of change of CSF Abeta42 using linear regression after adjusting for age, sex, BMI and ApoE4 status. LnAHIall and lnAHI4 were not associated with increases in ADPiB-mask most likely due to the small sample size although there was a trend for lnAHIall (F1,28=2.96, p=.09 and F1,28=2.32, n.s. respectively). CONCLUSION: In a sample of cognitively normal elderly, OSA was associated with markers of increased amyloid burden over the 2 year follow-up. Sleep fragmentation and/or intermittent hypoxia from OSA are likely candidate mechanisms. If confirmed, clinical interventions for OSA may be useful in preventing amyloid build-up in cognitively normal elderly.

PURPOSE:™ (single channel finger transmission pulse oximeter), compared to differences from night-night variability of OSA. METHODS:(apneas + hypopneas with ≥4% O2 dips/h or arousal surrogates). Baseline awake oxygen saturation, percent time < 90% O2 saturation (%time < 90%O2Sat), and O2 signal loss were compared between the two methods. RESULTS:(median (IQR) 0.5 (0.0, 2.6) vs. 2.1 (0.3, 9.7), p < 0.001), and the correlation was low (ICC = 0.2). CONCLUSIONS:OSA severity metrics predominantly dependent on change in oxygen saturation and metrics used in diagnosis of OSA (AHI4 and ODI) correlated well across devices tested. However, differences in cumulative oxygen desaturation measures (i.e., %time < 90%O2Sat) between the devices suggest that caution is needed when interpreting this metric particularly in populations likely to have significant hypoxia.