Faculty Bibliography

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.

STUDY OBJECTIVES/OBJECTIVE:Sleep apnea is associated with hypertension, and treatment may improve outcomes. We examine national burden of sleep apnea, rates of sleep apnea treatment, and whether racial/ethnic disparities exist among patients with hypertension. METHODS:Data from the National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS), 2005-2012, were analyzed (N = 417,950). We identified hypertension patient visits where sleep apnea diagnosis or complaint was recorded. Primary outcome measures were sleep study, medication, or behavioral therapy (diet, weight loss, or exercise counseling). We used multivariate logistic regression to examine treatment by demographic/clinical factors. RESULTS:Among patients with hypertension, sleep apnea was identified in 11.2-per-1,000 visits. Overall, patients with hypertension and a sleep disorder were referred for sleep study in 14.4% of visits, prescribed sleep medication in 11.2% of visits, and offered behavioral therapy in 34.8% of visits. Adjusted analyses show behavioral therapy more likely to be provided to obese patients than normal/overweight (OR = 4.96, 95%CI[2.93-8.38]), but less likely to be provided to smokers than nonsmokers (OR = 0.54, 95%CI[0.32-0.93]). Non-Hispanic blacks were less likely to receive medications than non-Hispanic whites (OR = 0.19, 95% CI[0.06-0.65]). CONCLUSIONS:In the U.S., sleep apnea were observed in a small proportion of hypertension visits, a population at high-risk for the disorder. One explanation for the low prevalence of sleep apnea observed in this patient population at high risk for the disorder is under-diagnosis of sleep related breathing disorders. Behavioral therapy was underutilized, and non-Hispanic Blacks were less likely to receive medications than non-Hispanic Whites.

Introduction: Increasing evidence suggests sleep can influence the risk for development of Alzheimer disease (AD), but the precise features of sleep architecture influencing this risk and the role of obstructive sleep apnea (OSA) in contributing to this risk remain only partially characterized. Current models of AD suggest that pathological changes, including the accumulation of proteins beta-amyloid (Ab) and tau, can occur years to even decades before clinical symptoms of memory impairment become evident. In this study, we examined the impact of OSA severity on longitudinal changes in Ab measured both in cerebrospinal fluid (CSF) and with brain PET imaging with Pittsburgh compound B (PiB). In subsets of individuals without significant OSA, we examined the impact of features of sleep architecture such as slow wave activity (SWA) and spindles on concentrations CSF Ab and tau at cross-section. Materials and Methods: 208 cognitively normal elderly subjects (68 +/- 7 years, CDR score = 0) received medical, neurological, and psychiatric evaluations, home polysomnography (PSG) for OSA severity, structural magnetic resonance imaging (MRI) scans, a lumbar puncture (LP) and/or PiB PET scans. A subset of 109 subjects completed a second LP 2.4 +/- 0.9 years after the first LP, and a subset of 34 subjects completed a second brain PiB PET scan 2.5 +/- 0.4 years after the first. A subset of 50 subjects without significant OSA (AHI4% < 15/hour) completed in-laboratory nocturnal PSG for measurements of sleep architecture. SWA was calculated using the average power density in the 0.5-4.0 Hz range at the F4- lead during full night EEG recordings. Spindles were isolated and quantified using DETOKS in which the EEG from the C3-lead was decomposed into oscillatory and non-oscillatory components. Oscillatory components were further scored for sleep spindles using threshold values in the frequency band of 11-16 Hz and time duration of 0.5 to 3 seconds. Results: OSA increased amyloid burden over the years, as a significant association was found between longitudinal decreases in CSF Ab42 and increasing OSA severity indices AHI-all (F1,88 = 4.26, p< .05) and AHI4% (F1,87 = 4.36, p< .05). This was corroborated by a trend toward longitudinal increases in brain PiB PET uptake positively associating with increasing OSA severity by AHI-all (F1,28 = 2.96, p=.09). At cross-section, in those subjects without significant OSA, low frontal SWA was significantly associated with high concentrations of CSF Ab42 and low sleep spindle counts and density were significantly associated with high levels of total and phosphorylated tau in the CSF

BACKGROUND: Automated single-channel spindle detectors, for human sleep EEG, are blind to the presence of spindles in other recorded channels unlike visual annotation by a human expert. NEW METHOD: We propose a multichannel spindle detection method that aims to detect global and local spindle activity in human sleep EEG. Using a non-linear signal model, which assumes the input EEG to be the sum of a transient and an oscillatory component, we propose a multichannel transient separation algorithm. Consecutive overlapping blocks of the multichannel oscillatory component are assumed to be low-rank whereas the transient component is assumed to be piecewise constant with a zero baseline. The estimated oscillatory component is used in conjunction with a bandpass filter and the Teager operator for detecting sleep spindles. RESULTS AND COMPARISON WITH OTHER METHODS: The proposed method is applied to two publicly available databases and compared with 7 existing single-channel automated detectors. F1 scores for the proposed spindle detection method averaged 0.66 (0.02) and 0.62 (0.06) for the two databases, respectively. For an overnight 6 channel EEG signal, the proposed algorithm takes about 4min to detect sleep spindles simultaneously across all channels with a single setting of corresponding algorithmic parameters. CONCLUSIONS: The proposed method attempts to mimic and utilize, for better spindle detection, a particular human expert behavior where the decision to mark a spindle event may be subconsciously influenced by the presence of a spindle in EEG channels other than the central channel visible on a digital screen.

This report summarizes the proceedings of the American Thoracic Society Workshop on the Noninvasive Identification of Inspiratory Flow Limitation in Sleep Studies held on May 16, 2015, in Denver, Colorado. The goal of the workshop was to discuss methods for standardizing the scoring of flow limitation from nasal cannula pressure tracings. The workshop began with presentations on the physiology underlying flow limitation, existing methods of scoring flow limitation, the effects of signal acquisition and filtering on flow shapes, and a review of the literature examining the adverse outcomes related to flow limitation. After these presentations, the results from online scoring exercises, which were crowdsourced to workshop participants in advance of the workshop, were reviewed and discussed. Break-out sessions were then held to discuss potential algorithms for scoring flow limitation. Based on these discussions, subsequent online scoring exercises, and webinars after the workshop, a consensus-based set of recommendations for a scoring algorithm for flow limitation was developed. Key conclusions from the workshop were: (1) a standardized and automated approach to scoring flow limitation is needed to provide a metric of nonepisodic elevated upper airway resistance, which can then be related to clinical outcomes in large cohorts and patient groups; (2) at this time, the most feasible method for standardization is by proposing a consensus-based framework, which includes scoring rules, developed by experts (3) hardware and software settings of acquisition devices, including filter settings, affect the shape of the flow curve, and should be clearly specified; and (4) a priority for future research is the generation of an open-source, expert-derived training set to encourage and support validation of automated flow limitation scoring algorithms.