Dupuy-McCauley, Kara

Abstract Introduction Tizanidine is an alpha-2 receptor adrenergic agonist employed for treatment of musculoskeletal pain and muscle spasticity. Drowsiness, xerostomia, and, less frequently, sleep disturbance are notable side effects. Central sleep apnea (CSA) occurs in patients taking other alpha-2 receptor agonists such as clonidine but the frequency of CSA among users of tizanidine is less well-known. Rarer still is the presence of central apneic episodes during wakefulness in patients without heart failure who have an intact brainstem and are not taking opioids or benzodiazepines. We report a case of a patient with central apneic episodes during wakefulness in the setting of tizanidine use. Report of case A 60-year-old white male was referred to our sleep center for sleep apnea. He was previously diagnosed with severe obstructive sleep apnea (apnea-hypopnea index of 104 events per hour) but was not adherent to continuous positive airway pressure (CPAP) due to a previous head injury which made use of CPAP straps intolerably painful. Thus, he had undergone a modified uvulopalatopharyngoplasty 3 months prior to evaluation. Despite UPPP he continued to have excessive daytime sleepiness. A repeat polysomnogram revealed frequent central apneic episodes during periods of wakefulness that did not persist after sleep onset. The patient had taken his nightly tizanidine 8 mg prior to testing. Echocardiogram prior to testing showed mild diastolic dysfunction and brain magnetic resonance imaging was unremarkable. A polysomnogram was repeated 1 month later, this time with tizanidine held for 1 week prior to testing. Wake-onset central apneic episodes had resolved without any other changes in medication or health status. Conclusion Certain medications such as opioids, benzodiazepines, and baclofen are known to induce CSA. However, to the best of our knowledge this is the first case of a commonly prescribed alpha-2 agonist implicated in the development of wake-onset central apneic episodes. More study is needed to elucidate the impact of tizanidine on ventilatory function in the wake and sleep states and whether similar effects may occur among other centrally acting medications. Support (if any)

Abstract Introduction Despite AASM scoring guidelines encouraging classifying hypopneas as central or obstructive, classification is underutilized in practice. However, without that effort patients may receive an incorrect primary diagnosis and suboptimal treatment. The remedē® System Pivotal Trial studied transvenous phrenic nerve stimulation (TPNS) to treat adult patients with moderate to severe central sleep apnea (CSA). Entry criteria required apnea hypopnea index (AHI)≥20 with the central apnea index (CAI) greater than the obstructive apnea index and obstructive apneas< 20% of AHI but did not consider hypopnea differentiation. This analysis re-examined sleep studies from the trial to assess how hypopnea classification might lead to better patient selection for this therapy. Methods Hypopneas were classified as central versus obstructive by a sleep core laboratory following a modified version of AASM recommended criteria. The AHI composition was assessed at baseline and after 6 months of therapy. Results At baseline, 91% (138/151) of patients had ≥50% of events classified as central when accounting for hypopnea classification. If all hypopneas were assumed to be obstructive, only 63% (95/151) would have had ≥50% central events. Additionally, 95% (144/151) of patients had central AHI ≥15/hour, compared to 73% (110/151) with a central apnea index (CAI) ≥15/hour. The likelihood of achieving a ≥50% AHI reduction increased with the percentage of baseline events that were central: responder rates were 37.5% for patients with < 50% central events at baseline, incrementally increasing to 76.5% for those with ≥90% central events. At 6 months, the residual AHI predominantly consisted of obstructive events. Central events decreased by 89% with treatment, from a baseline median of 32/hour [1st and 3rd quartiles: 22, 50]. Obstructive apneas rose by 2/hour and obstructive hypopneas increased by 2/hour from a baseline median of 5 obstructive events/hour [2, 12]. Conclusion Distinguishing central from obstructive hypopneas is required to accurately determine if a patient has central sleep apnea/Cheyne Stokes respiration, and is crucial for epidemiologic studies, appropriate therapy selection, and managing patient expectations about treatment outcomes. This analysis suggests that accurate hypopnea classification may prevent disqualification of patients who could benefit from TPNS therapy, which effectively treats central sleep apnea syndrome. Support (if any) ZOLL Respicardia, Inc.

Abstract Introduction Identifying central sleep apnea (CSA) during home sleep apnea testing is important to guide appropriate treatment for sleep-disordered breathing (SDB) and underlying cardiovascular conditions, including heart failure and atrial fibrillation. SANSA (Huxley Medical, Inc.) is a multi-diagnostic chest-worn monitor capable of detecting SDB, cardiac arrhythmias, and heart function. Using polysomnography (PSG) as a reference, we developed a machine learning (ML) method to classify respiratory events from this monitor as central or obstructive. Methods Data was analyzed from ninety-five subjects with suspected SDB who wore the chest monitor simultaneously with PSG overnight. To address known scoring heterogeneity of CSA, PSG records were scored for central apneas by two core laboratories (Core 1 and Core 2). Core 1 annotations from twenty-eight records were first used to train a random forest classifier to differentiate obstructive (N=680) and central events (N=388). The model used oximetry, respiratory effort, and snoring to classify events based on effort, duration, and other features. A five-fold cross validation was used to evaluate event-level performance. The model was then used to estimate subject-level CAI for all subjects and compared with Core 2 scores. Results Algorithm event-level sensitivity and specificity to detect central events was 72.7% and 81.0%. Subject-level CAI for all records between the chest monitor and Core 2 had a correlation coefficient of 0.90 and root mean squared error (RMSE) of 4.6 events/hour, versus 0.82 and 4.7 events/hour comparing Core 1 and Core 2. Sensitivity and specificity to detect CAI≥10 events/hour was 80.0% (4/5) and 98.9% (89/90), compared to 100% (3/3) and 98.9% (91/92) for CAI≥15. Conclusion An ML algorithm to differentiate obstructive and central events collected from the chest-worn monitor demonstrated favorable event-level performance and comparable CAI agreement to that between two PSG core laboratories. Home-based CSA detection alongside cardiac monitoring could identify high risk patients for expedited therapy, cardiology referral, or follow-up PSG. These results motivate further validation in a larger cohort as well as investigation of outcomes related to time to evaluation and management. Support (if any) National Science Foundation; Georgia Research Alliance; Huxley Medical, Inc.

Obesity hypoventilation syndrome (OHS) can often be underdiagnosed or misdiagnosed and has been shown to pose significant risks in perioperative situations. Patients with OHS have a higher prevalence of baseline morbid conditions like hypertension, congestive heart failure (CHF), diabetes mellitus, atrial fibrillation, and pulmonary hypertension (PH), which contribute to adverse postoperative outcomes. The potential challenges include difficult intubation and loss of airway, postoperative respiratory failure, worsening heart failure, pulmonary hypertensive crisis, and opioid-induced respiratory depression (OIRD). It is, therefore, important to screen all obese patients for obstructive sleep apnea (OSA) and OHS before elective surgical procedures. The aim of this review is to discuss the preoperative screening and evaluation and safe anesthetic and up-to-date ventilatory management of this complex group of patients. This review also intends to increase the awareness of OHS in the adult population among hospitalists, surgeons, and cardiologists who may find themselves taking care of these patients in complex multidisciplinary settings.

Sleep disturbances are common in chronic liver disease and significantly impact patient outcomes and quality of life. The severity and nature of sleep disturbances vary by liver disease etiology and severity. While there is ongoing research into the association between liver disease and sleep-wake dysfunction, the underlying pathophysiology varies and, in many cases, is poorly understood. Liver disease is associated with alterations in thermoregulation, inflammation, and physical activity, and is associated with disease-specific complications, such as HE, that may directly affect sleep. In this article, we review the relevant pathophysiologic processes, disease-specific sleep-wake disturbances, and clinical management of CLD-associated sleep-wake disturbances.

ABSTRACT Background Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA). Methods Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence‐based review (EBR), or evidence‐based review with recommendations (EBR‐R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus. Results The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA‐associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated. Conclusion This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence‐based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.