International Consensus Statement on Obstructive Sleep Apnea.

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.

Evaluation and Treatment of Central Sleep Apnea in Patients with Heart Failure.

Sleep-disordered breathing (SDB) is a common comorbidity in patients with heart failure (HF). Prevalence of the most common subtypes of SDB, central sleep apnea (CSA) and obstructive sleep apnea (OSA), is increasing, which is concerning due to the association of SDB with increased mortality in patients with HF. Despite an increasing burden of CSA in HF, it is difficult to detect using current diagnostic tools and the treatment modalities are limited by variable efficacy and patient adherence. Though positive airway pressure therapies remain the cornerstone of OSA treatment, the management of CSA in the setting of HF continues to evolve. The association of the presence of CSA with worse prognosis in HF patients warrants the need for routine screening for signs and symptoms of CSA in this population. In this review, we examine the connection between CSA and HF, and highlight advancements in timely diagnostics, treatment modalities, and strategies to promote facilitation of compliance in this high-risk cohort.

A comparison of 2 visual methods for classifying obstructive vs central hypopneas.

STUDY OBJECTIVES: Rules for classifying apneas as obstructive, central, or mixed are well established. Although hypopneas are given equal weight when calculating the apnea-hypopnea index, classification is not standardized. Visual methods for classifying hypopneas have been proposed by the American Academy of Sleep Medicine and by Randerath et al (Sleep. 2013;36[3]:363-368) but never compared. We evaluated the clinical suitability of the 2 visual methods for classifying hypopneas as central or obstructive. METHODS: Fifty hypopnea-containing polysomnographic segments were selected from patients with clear obstructive or clear central physiology to serve as standard obstructive or central hypopneas. These 100 hypopnea-containing polysomnographic segments were deidentified, randomized, and scored by 2 groups. We assigned 1 group to use the American Academy of Sleep Medicine criteria and the other the Randerath algorithm. After a washout period, re-randomized hypopnea-containing polysomnographic segments were scored using the alternative method. We determined the accuracy (agreement with standard), interrater (Fleiss's κ), and intrarater agreement (Cohen's κ) for obtained scores. RESULTS: Accuracy of the 2 methods was similar: 67% vs 69.3% for Randerath et al and the American Academy of Sleep Medicine, respectively. Cohen's κ was 0.01-0.75, showing that some raters scored similarly using the 2 methods, while others scored them markedly differently. Fleiss's κ for the American Academy of Sleep Medicine algorithm was 0.32 (95% confidence interval, 0.29-0.36) and for the Randerath algorithm was 0.27 (95% confidence interval, 0.23-0.30). CONCLUSIONS: More work is needed to discover a noninvasive way to accurately characterize hypopneas. Studies like ours may lay the foundation for discovering the full spectrum of physiologic consequences of obstructive sleep apnea and central sleep apnea.

Prevalence and Sources of Errors in Positive Airway Pressure Therapy Provisioning.

STUDY OBJECTIVES: The prevalence and mechanism of medication errors have been well characterized in the literature. However, no prior studies have investigated the frequency and characteristics of errors in the positive airway pressure (PAP) therapy provisioning process when treating patients with sleep-disordered breathing. Just as medication errors may result in unwanted outcomes, it might be anticipated that errors in providing PAP to patients might lead to suboptimal outcomes. Our study seeks to examine the characteristics and frequency of PAP provisioning errors. METHODS: This was a retrospective analysis of a cohort of patients in whom sleep-disordered breathing had been diagnosed and subsequently PAP therapy was prescribed. At a 90-day return visit, the PAP therapy the patient was receiving was compared with the intended therapy. Discrepancies were categorized as either prescribing errors (the prescription did not match the intended modality or settings), or setup errors (the modality or settings did not match the prescription). RESULTS: The overall PAP provisioning error rate was 8%, with errors most commonly occurring during the set-up process. In univariate analysis, insurance type (P = .003), treatment modality (P = .002), and device brand (P = .05) were associated with error and remained significant in multivariate analysis (model fit P = .002). Compliance, residual AHI, and difference in Epworth Sleepiness Scale were not affected by the presence of error. CONCLUSIONS: PAP provisioning errors are common and might contribute to poor treatment outcomes. Errors might be reduced by standardizing terminology across devices, standardizing prescription forms to improve clarity, and by enhanced quality assurance at durable medical equipment suppliers.