Faculty Bibliography

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 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.

The diagnostic criteria for obstructive sleep apnea (OSA) in adults, as defined in the International Classification of Sleep Disorders, Third Edition, requires an increased frequency of obstructive respiratory events demonstrated by in-laboratory, attended polysomnography (PSG) or a home sleep apnea test (HSAT). However, there are currently two hypopnea scoring criteria in The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications (AASM Scoring Manual). This dichotomy results in differences among laboratory reports, patient treatments and payer policies. Confusion occurs regarding recognizing and scoring "arousal-based respiratory events" during OSA testing. "Arousal-based scoring" recognizes hypopneas associated with electroencephalography-based arousals, with or without significant oxygen desaturation, when calculating an apnea-hypopnea index (AHI), or it includes respiratory effort-related arousals (RERAs), in addition to hypopneas and apneas, when calculating a respiratory disturbance index (RDI). Respiratory events associated with arousals, even without oxygen desaturation, cause significant, and potentially dangerous, sleep apnea symptoms. During PSG, arousal-based respiratory scoring should be performed in the clinical evaluation of patients with suspected OSA, especially in those patients with symptoms of excessive daytime sleepiness, fatigue, insomnia, or other neurocognitive symptoms. Therefore, it is the position of the AASM that the RECOMMENDED AASM Scoring Manual scoring criteria for hypopneas, which includes diminished airflow accompanied by either an arousal or ≥ 3% oxygen desaturation, should be used to calculate the AHI. If the ACCEPTABLE AASM Scoring Manual criteria for scoring hypopneas, which includes only diminished airflow plus ≥ 4% oxygen desaturation (and does not allow for arousal-based scoring alone), must be utilized due to payer policy requirements, then hypopneas as defined by the RECOMMENDED AASM Scoring Manual criteria should also be scored. Alternatively, the AASM Scoring Manual includes an option to report an RDI which also provides an assessment of the sleep-disordered breathing that results in arousal from sleep. Furthermore, given the inability of most HSAT devices to capture arousals, a PSG should be performed in any patient with an increased risk for OSA whose HSAT is negative. If the PSG yields an AHI of 5 or more events/h, or if the RDI is greater than or equal to 5 events/h, then treatment of symptomatic patients is recommended to improve quality of life, limit neurocognitive symptoms, and reduce accident risk.

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.

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.