In this issue of the Journal of Clinical Sleep Medicine, the Sleep Apnea Definitions (SAD) task force of the American Academy of Sleep Medicine (AASM) redefines many of the respiratory rules found in the 2007 AASM Manual for the Scoring of Sleep and Associated Events. This task force labored over a two-year period, analyzing the recent literature pertaining to respiratory events and sensor technology, and striving to reach consensus on a new set of respiratory rules. The paper details some significant changes including a single definition of a hypopnea. In addition, there is now the option to score hypopneas as central or obstructive. There is also greater concordance between adult and pediatric scoring rules for various respiratory events. (Please refer to the forthcoming new version of the scoring manual for the final version of the rules for scoring respiratory events.)

Critically ill patients frequently experience poor sleep, characterized by frequent disruptions, loss of circadian rhythms, and a paucity of time spent in restorative sleep stages. Factors that are associated with sleep disruption in the intensive care unit (ICU) include patient-ventilator dysynchrony, medications, patient care interactions, and environmental noise and light. As the field of critical care increasingly focuses on patients' physical and psychological outcomes following critical illness, understanding the potential contribution of ICU-related sleep disruption on patient recovery is an important area of investigation. This review article summarizes the literature regarding sleep architecture and measurement in the critically ill, causes of ICU sleep fragmentation, and potential implications of ICU-related sleep disruption on patients' recovery from critical illness. With this background information, strategies to optimize sleep in the ICU are also discussed.

© 2013 by the American College of Medical Quality. Critically ill patients commonly experience poor sleep quality in the intensive care unit (ICU) because of various modifiable factors. To address this issue, an ICU-wide, multifaceted quality improvement (QI) project was undertaken to promote sleep in the Johns Hopkins Hospital Medical ICU (MICU). To supplement previously published results of this QI intervention, the present article describes the specific QI framework used to develop and implement this intervention, which consists of 4 steps: (a) summarizing the evidence to create a list of sleep-promoting interventions, (b) identifying and addressing local barriers to implementation, (c) selecting performance measures to assess intervention adherence and patient outcomes, and (d) ensuring that all patients receive the interventions through staff engagement and education and regular project evaluation. Measures of performance included daily completion rates of daytime and nighttime sleep improvement checklists and completion rates of individual interventions. Although long-term adherence and sustainability pose ongoing challenges, this model provides a foundation for future ICU sleep promotion initiatives.

Background: Poor sleep is common in the ICU setting and may represent a modifiable risk factor for patient participation in ICU-based physical therapy (PT) interventions. This study evaluates the association of perceived sleep quality, delirium, sedation, and other clinically important patient and ICU factors with participation in physical therapy (PT) interventions. Method: This was a secondary analysis of a prospective observational study of sleep in a single academic medical ICU (MICU). Perceived sleep quality was assessed using the Richards-Campbell Sleep Questionnaire (RCSQ) and delirium was assessed using the Confusion Assessment Method for the ICU (CAM-ICU). Other covariates included demographics, pre-hospitalization ambulation status, ICU admission diagnosis, daily mechanical ventilation status, and daily administration of benzodiazepines and opioids via bolus and continuous infusion. Associations with participation in PT interventions were assessed among patients eligible for PT using a multinomial Markov model with robust variance estimates. Results: Overall, 327 consecutive MICU patients completed ≥1 assessment of perceived sleep quality. After adjusting for all covariates, daily assessment of perceived sleep quality was not associated with transitioning to participate in PT the following day (relative risk ratio [RRR] 1.02, 95 % CI 0.96-1.07, p = 0.55). However, the following factors had significant negative associations with participating in subsequent PT interventions: delirium (RRR 0.58, 95 % CI 0.41-0.76, p <0.001), opioid boluses (RRR 0.68, 95 % CI 0.47-0.99, p = 0.04), and continuous sedation infusions (RRR 0.58, 95 % CI 0.40-0.85, p = 0.01). Additionally, in patients with delirium, benzodiazepine boluses further reduced participation in subsequent PT interventions (RRR 0.25, 95 % CI 0.13-0.50, p <0.001). Conclusions: Perceived sleep quality was not associated with participation in PT interventions the following day. However, continuous sedation infusions, opioid boluses, and delirium, particularly when occurring with administration of benzodiazepine boluses, were negatively associated with subsequent PT interventions and represent important modifiable factors for increasing participation in ICU-based PT interventions.

The purpose of the Society of Anesthesia and Sleep Medicine guideline on preoperative screening and assessment of adult patients with obstructive sleep apnea (OSA) is to present recommendations based on the available clinical evidence on the topic where possible. As very few well-performed randomized studies in this field of perioperative care are available, most of the recommendations were developed by experts in the field through consensus processes involving utilization of evidence grading to indicate the level of evidence upon which recommendations were based. This guideline may not be appropriate for all clinical situations and all patients. The decision whether to follow these recommendations must be made by a responsible physician on an individual basis. Protocols should be developed by individual institutions taking into account the patients' conditions, extent of interventions and available resources. This practice guideline is not intended to define standards of care or represent absolute requirements for patient care. The adherence to these guidelines cannot in any way guarantee successful outcomes and is rather meant to help individuals and institutions formulate plans to better deal with the challenges posed by perioperative patients with OSA. These recommendations reflect the current state of knowledge and its interpretation by a group of experts in the field at the time of publication. While these guidelines will be periodically updated, new information that becomes available between updates should be taken into account. Deviations in practice from guidelines may be justifiable and such deviations should not be interpreted as a basis for claims of negligence.

This study sought to determine the cardiovascular physiologic correlates of sleep-disordered breathing (SDB) in American-style football (ASF) participants using echocardiography, vascular applanation tonometry, and peripheral arterial tonometry. Forty collegiate ASF participants were analyzed at pre- and postseason time points with echocardiography and vascular applanation tonometry. WatchPAT (inclusive of peripheral arterial tonometry) used to assess for SDB was then performed at the postseason time point. Twenty-two of 40 (55%) ASF participants demonstrated SDB with an apnea-hypopnea index (pAHI) ≥5. ASF participants with SDB were larger (109 ± 20 vs 92 ± 14 kg, p = 0.004) and more likely linemen position players (83% vs 50%, p = 0.03). Compared with those without SDB, ASF participants with SDB demonstrated relative impairments in left ventricular diastolic and vascular function as reflected by lower lateral e′ (14 ± 3 vs 17 ± 3 cm/s, p = 0.007) and septal e′ (11 ± 2 vs 13 ± 2 cm/s, p = 0.009) tissue velocities and higher pulse wave velocity (5.4 ± 0.9 vs 4.8 ± 0.5 m/s, p = 0.02). In the total cohort, there were significant positive correlations between pAHI and pulse wave velocity (r = 0.42, p = 0.008) and inverse correlations between pAHI and the averaged e′ tissue velocities (r = −0.42, p = 0.01). In conclusion, SDB is highly prevalent in youthful collegiate ASF participants and associated with relative impairments in cardiac and vascular function. Targeted efforts to identify youthful populations with SDB, including ASF participants, and implement SDB treatment algorithms, represent important future clinical directives.