Faculty Bibliography

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.

The ridesharing-or ride-hailing-industry has grown exponentially in recent years, transforming quickly into a fee-for-service, unregulated taxi industry. While riders are experiencing the benefits of convenience and affordability, two key regulatory and safety issues deserve consideration. First, individuals who work as drivers in the ridesharing industry are often employed in a primary job, and they work as drivers during their "off" time. Such a schedule may lead to driving after extended periods of wakefulness or during nights, both of which are factors that increase the risk of drowsy driving accidents. Second, these drivers are often employed as "independent contractors," and therefore they are not screened for medical problems that can reduce alertness, such as obstructive sleep apnea. Some ridesharing companies now require a rest period after an extended driving shift. This measure is encouraging, but it is insufficient to impact driving safety appreciably, particularly since many of these drivers are already working extended hours and tend to drive at non-traditional times when sleepiness may peak. Therefore, it is the position of the American Academy of Sleep Medicine (AASM) that fatigue and sleepiness are inherent safety risks in the ridesharing industry. The AASM calls on ridesharing companies, government officials, medical professionals, and law enforcement officers to work together to address this public safety risk. A collaborative effort is necessary to understand and track the scope of the problem, provide relevant education, and mitigate the risk through thoughtful regulation and effective fatigue risk management systems.

Consumer sleep technologies (CSTs) are widespread applications and devices that purport to measure and even improve sleep. Sleep clinicians may frequently encounter CST in practice and, despite lack of validation against gold standard polysomnography, familiarity with these devices has become a patient expectation. This American Academy of Sleep Medicine position statement details the disadvantages and potential benefits of CSTs and provides guidance when approaching patient-generated health data from CSTs in a clinical setting. Given the lack of validation and United States Food and Drug Administration (FDA) clearance, CSTs cannot be utilized for the diagnosis and/or treatment of sleep disorders at this time. However, CSTs may be utilized to enhance the patient-clinician interaction when presented in the context of an appropriate clinical evaluation. The ubiquitous nature of CSTs may further sleep research and practice. However, future validation, access to raw data and algorithms, and FDA oversight are needed.

BACKGROUND:Sleep apnea is an underdiagnosed condition in patients with heart failure. Efficient identification of sleep apnea is needed, as treatment may improve heart failure-related outcomes. Currently, use of portable sleep monitoring in hospitalized patients and those at risk for central sleep apnea is discouraged. This study examined whether portable sleep monitoring with respiratory polygraphy can accurately diagnose sleep apnea in patients hospitalized with decompensated heart failure. METHODS:Hospitalized patients with decompensated heart failure underwent concurrent respiratory polygraphy and polysomnography. Both recordings were scored for obstructive and central disordered breathing events in a blinded fashion, using standard criteria, and the apnea-hypopnea index (AHI) was determined. Pearson's correlation coefficients and Bland-Altman plots were used to examine the concordance among the overall, obstructive, and central AHI values derived by respiratory polygraphy and polysomnography. RESULTS:The sample consisted of 53 patients (47% women) with a mean age of 59.0 years. The correlation coefficient for the overall AHI from the two diagnostic methods was 0.94 (95% CI, 0.89-0.96). The average difference in AHI between the two methods was 3.6 events/h. Analyses of the central and obstructive AHI values showed strong concordance between the two methods, with correlation coefficients of 0.98 (95% CI, 0.96-0.99) and 0.91 (95% CI, 0.84-0.95), respectively. Complete agreement in the classification of sleep apnea severity between the two methods was seen in 89% of the sample. CONCLUSIONS:Portable sleep monitoring can accurately diagnose sleep apnea in hospitalized patients with heart failure and may promote early initiation of treatment.

The diagnosis and effective treatment of obstructive sleep apnea (OSA) in adults is an urgent health priority. It is the position of the American Academy of Sleep Medicine (AASM) that only a medical provider can diagnose medical conditions such as OSA and primary snoring. Throughout this statement, the term "medical provider" refers to a licensed physician and any other health care professional who is licensed to practice medicine in accordance with state licensing laws and regulations. A home sleep apnea test (HSAT) is an alternative to polysomnography for the diagnosis of OSA in uncomplicated adults presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. It is also the position of the AASM that: the need for, and appropriateness of, an HSAT must be based on the patient's medical history and a face-to-face examination by a medical provider, either in person or via telemedicine; an HSAT is a medical assessment that must be ordered by a medical provider to diagnose OSA or evaluate treatment efficacy; an HSAT should not be used for general screening of asymptomatic populations; diagnosis, assessment of treatment efficacy, and treatment decisions must not be based solely on automatically scored HSAT data, which could lead to sub-optimal care that jeopardizes patient health and safety; and the raw data from the HSAT device must be reviewed and interpreted by a physician who is either board-certified in sleep medicine or overseen by a board-certified sleep medicine physician.