Faculty Bibliography

BACKGROUND:Portable monitoring is a convenient means for diagnosing sleep apnea. However, data on whether one night of monitoring is sufficiently precise for the diagnosis of sleep apnea are limited. RESEARCH QUESTION:The current study sought to determine the variability and misclassification in disease severity over three consecutive nights in a large sample of patients referred for sleep apnea. METHODS:A sample of 10,340 adults referred for sleep apnea testing was assessed. A self-applied type III monitor was used for three consecutive nights. The apnea-hypopnea index (AHI) was determined for each night, and a reference AHI was computed by using data from all 3 nights. Pairwise correlations and the proportion misclassified regarding disease severity were computed for each of the three AHI values against the reference AHI. RESULTS:Strong correlations were observed between the AHI from each of the 3 nights (r = 0.87-0.89). However, substantial within-patient variability in the AHI and significant misclassification in sleep apnea severity were observed based on any 1 night of monitoring. Approximately 93% of the patients with a normal study on the first night and 87% of those with severe sleep apnea on the first night were correctly classified compared with the reference derived from all three nights. However, approximately 20% of the patients with mild and moderate sleep apnea on the first night were misdiagnosed either as not having sleep apnea or as having mild disease, respectively. CONCLUSIONS:In patients with mild to moderate sleep apnea, one night of portable testing can lead to misclassification of disease severity given the substantial night-to-night variability in the AHI.

Rosen CL, Aurora RN, Kapur VK, et al. Supporting American Academy of Neurology’s new clinical practice guideline on evaluation and management of insomnia in children with autism. J Clin Sleep Med. 2020;16(6):989–990.

None/UNASSIGNED:Physician burnout is a serious and growing threat to the medical profession and may undermine efforts to maintain a sufficient physician workforce to care for the growing and aging patient population in the U.S. Burnout involves a host of complex underlying associations and potential for risk. While prevalence is unknown, recent estimates of physician burnout are quite high, approaching 50% or more, with mid-career physicians at highest risk. Sleep deprivation due to shift-work schedules, high workload, long hours, sleep interruptions, and insufficient recovery sleep have been implicated in the genesis and perpetuation of burnout. Maladaptive attitudes regarding sleep and endurance also may increase the risk for sleep deprivation among attending physicians. While duty-hour restrictions have been instituted to protect sleep opportunity among trainees, virtually no such effort has been made for attending physicians who have completed their training or practicing physicians in non-academic settings. It is the position of the AASM that a critical need exists to evaluate the roles of sleep disruption, sleep deprivation, and circadian misalignment in physician well-being and burnout. Such evaluation may pave the way for the development of effective countermeasures that promote healthy sleep, with the goal of reducing burnout and its negative impacts such as a shrinking physician workforce, poor physician health and functional outcomes, lower quality of care, and compromised patient safety.

None/UNASSIGNED:Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during a polysomnogram (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.

There is a complex relationship among opioids, sleep and daytime function. Patients and medical providers should be aware that chronic opioid therapy can alter sleep architecture and sleep quality as well as contribute to daytime sleepiness. It is also important for medical providers to be cognizant of other adverse effects of chronic opioid use including the impact on respiratory function during sleep. Opioids are associated with several types of sleep-disordered breathing, including sleep-related hypoventilation, central sleep apnea (CSA), and obstructive sleep apnea (OSA). Appropriate screening, diagnostic testing, and treatment of opioid-associated sleep-disordered breathing can improve patients' health and quality of life. Collaboration among medical providers is encouraged to provide high quality, patient-centered care for people who are treated with chronic opioid therapy.

STUDY OBJECTIVES:Self-reported sleepiness is common in patients with obstructive sleep apnea (OSA) and is being increasingly recognized as an effect modifier of the association between OSA and cardiovascular outcomes. However, data on whether sleepiness modifies the association between OSA and glycemic outcomes are lacking. The current study sought to characterize the association between glycemic control and sleepiness in people with OSA and type 2 diabetes. METHODS:Adults with non-insulin requiring type 2 diabetes and undiagnosed moderate to severe OSA were recruited from the community. Demographic data, Epworth Sleepiness Scale (ESS), hemoglobin A1c (HbA1c), as well a type III home sleep test were obtained. The association between self-reported sleepiness and glycemic control was examined using quantile regression. RESULTS:or in women of any BMI category. CONCLUSIONS:The association between self-reported sleepiness and glycemic control in people with type 2 diabetes and moderate to severe OSA varies a function of BMI and sex. The noted differences in association should be considered when assessing possible treatment effects of therapy for OSA on metabolic outcomes.