Non-sleep Specialists Research Articles

A clinical algorithm for diagnosis and treatment of insomnia in adults: an updated review.

Difficulty falling asleep and/or maintaining sleep are common complaints in patients visiting medical clinics. Insomnia can occur alone or in combination with other medical or psychiatric disorders. Diagnosis and management of insomnia at times are perplexing. This updated study review aimed at a clinical algorithm for diagnosis and treatment of insomnia in adults. We developed an easy-to-apply algorithm to diagnose and manage insomnia that can be used by general practitioners and non-sleep specialists. To this end, our team reviewed the previous studies to determine the prevalence, evaluation, and treatment of insomnia. We used the results to develop a clinical algorithm for diagnosing and managing insomnia.Insomnia occurs in a short (less than 3months duration) or chronic form (≥3months duration). Insomnia management includes both pharmacological and non-pharmacological interventions. There is ample research evidence for the impact of a variety of non-pharmacological treatments, but both types of treatments can be used for each patient. If there are any contradictions in the diagnosis process, therapists should use objective instruments, such as polysomnography, but they should not be in a hurry to use these instruments.

Parental experiences in navigating health services for paediatric residual obstructive sleep apnoea: An exploratory qualitative descriptive study.

To explore parents' experiences and perceptions regarding engagement in health services for managing residual paediatric obstructive sleep apnoea (OSA) across levels of care. Qualitative description guided study design. Data were collected through semi-structured interviews with parents of children diagnosed with residual OSA at a university-based sleep clinic. The relevant literature informed the interview guide and was piloted before data collection. Inductive, manifest content analysis was used to describe parents' perceptions and experiences using data-driven categories and sub-categories. Several strategies were employed to ensure rigour in this study. Eight interviews were conducted. Parents' views were organized into five categories: awareness of the sleep issue, interaction with non-sleep specialists, interaction with sleep specialists, interaction with dental professionals, and further actions and support. Parents reported several engagement issues due to their interactions with different care providers. These issues included having to personally identify and raise the sleep problem, feeling that care providers did not take this problem seriously, waiting for an extended period to be referred for sleep services, and receiving conflicting or insufficient treatment recommendations. Overall, parents perceived that their actions and the services received across levels of care were not effective enough to address paediatric OSA. Based on this exploratory qualitative descriptive research, along with developing evidence-based clinical guidelines for paediatric OSA screening and management tailored to different levels of care, strategies intended to improve the engagement of patients and care providers in addressing paediatric OSA should be developed and empirically tested.

Machinelearning-Basedmodelforprediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness.

Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be overlooked. Machine learning (ML) models can enable the early detection of these conditions, which has never been applied for diagnosis of NT1. The study aimed to develop ML prediction models to help non-sleep specialist clinicians identify high probability of comorbid NT1 in patients with OSA early. Totally, clinical features of 246 patients with OSA in three sleep centers were collected and analyzed for the development of nine ML models. LASSO regression was used for feature selection. Various metrics such as the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA) were employed to evaluate and compare the performance of these ML models. Model interpretability was demonstrated by Shapley Additive explanations (SHAP). Based on the analysis of AUC, DCA, and calibration curves, the Gradient Boosting Machine (GBM) model demonstrated superior performance compared to other machine learning (ML) models. The top five features used in the GBM model, ranked by feature importance, were age of onset, total limb movements index, sleep latency, non-REM (Rapid Eye Movement)sleepstage 2 and severity of OSA. The study yielded a simple and feasible screening ML-based model for the early identification of NT1 in patients with OSA, which warrants further verification in more extensive clinical practices.

International palate surgery questionnaire.

This international study aimed at determining current routine palate surgeries and surgical methods adopted by otolaryngologists who practice surgical management ofobstructive sleep apnea (OSA). An international online survey was developed with the collaboration of the YO-IFOS (Young Otolaryngologists-International Federation of Otorhinolaryngological Societies) to assess the current routines in palatal procedures. The surgeons were asked 33 multiple-choice questions. A total of 141 sleep surgeons answered the questionnaire, of whom 27% were from Africa, 30% from Asia, 24% from Centre-South America, and 19% from Europe. According to otolaryngology surgical specialties, 51% were sleep surgeons, 31% general ENTs, 8% Rhinologists, 7% Head & Neck surgeons, 2% otologists, and 1% maxillofacial surgeons. Of the 141 respondents, 51% answered they were sleep specialists, whereas 49% were non-sleep specialists. According to specific medical degree, 38% were specialists, 33% were consultants, 25% were professors, and 4% were residents or trainees. This study gives an overview of the current surgical practice in OSA management in otolaryngology in different countries.

CPAP Therapeutic Options for Obstructive Sleep Apnea.

IntroductionThere are many options available to patients who are placed on constant positive airway pressure (CPAP) for obstructive sleep apnea. Despite the success of CPAP in correcting apnea, a significant number of patients have difficulty with the therapy. A large number of those patients who have difficulty stop therapy and are often labeled as “CPAP Failure”. Non-sleep specialists may view CPAP therapy as a singular course of treatment, but there are many ways CPAP may be ordered for a patient. Each patient experiences a unique set of options that constitute a unique order set.MethodsIn order to demonstrate the magnitude of the possible options, estimates of the number of unique order sets were calculated. The author chose individual order options and the number of selections possible within each option. The calculated sets included a “Generous, Limited and Minimal” number of selections for each option. Calculations were done separately for standard CPAP and for auto-adjusting CPAP. Additional calculations were performed using the number of commercially available masks in the United States.ResultsThe maximum number of unique order sets was seen using a standard CPAP combined with commercially available masks: 49,152 unique order sets. The fewest number of unique order sets were seen with the auto-adjusting CPAP and the “Minimal” selections: 288 unique order sets.DiscussionThere are a large number of unique CPAP orders that a patient may experience. CPAP treatment is not a singular or simple therapy. When evaluating obstructive sleep apnea patients with histories of CPAP failure or prior difficulty with CPAP, paying close attention to the patient’s treatment experiences may help explain a significant number of those patients’ CPAP therapy problems.

1178 Predictors Of Being Seen By A Board-certified Sleep Medicine Provider

Abstract Introduction Although several studies have evaluated the impact of board-certification in sleep medicine regarding obstructive sleep apnea treatment outcomes, no studies to date have identified predictive factors to determine which patients are evaluated by board-certified sleep medicine providers (BCSMP) in the clinical practice. Thus, the purpose of this study was to identify predictors of being seen by a BCSMP, relative to non-sleep specialist providers. Methods Our data source was a random 5% sample of Medicare administrative claims data from 2006-2013. Sleep disorder diagnoses such as insomnia, obstructive sleep apnea, restless legs syndrome, hypersomnias, and parasomnias, as well as medical comorbidities including cardiovascular, cerebrovascular, mood, pulmonary, and neurological disorders, were operationalized using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Demographic data were obtained from the claims. BCSMP were identified using a novel cross-matching approach based on National Provider Identifier (NPI). Results A total of 57,209 Medicare beneficiaries received a sleep disorder diagnosis between 2006-2013, but only 1,279 (2.2%) of these individuals were ever seen by a BCSMP. Within a multivariate logistic regression model, male gender, asthma, and heart failure were significantly associated with being seen by a BCSMP. Additionally, BCSMP were more likely to evaluate patients with two or more sleep diagnoses. Conclusion Complexity of sleep disorders and cardiovascular and lung comorbidities were predictive of being seen by a BCSMP. These results demonstrate the importance of BCSMPs in caring for complex sleep medicine patients. Support This research was supported by an AASM Strategic Research Award from the AASM Foundation to the University of Maryland, Baltimore (PI: EMW).

0640 Initial Sleep Center Evaluation and Follow Up Improves Positive Airway Pressure (PAP) Therapy Adherence When Compared to Direct Referrals Without Sleep Physician Follow Up: A Retrospective Study

Abstract Introduction Obstructive sleep apnea (OSA) affects 26% of adults and positive airway pressure (PAP) is the gold-standard of therapy. Factors affecting PAP adherence—use >4 hours in a 24-hour period—have been studied extensively. We compared of the three months (or other time frame) PAP adherence between patients seen by a sleep specialist prior to OSA diagnosis versus patients referred directly for OSA testing by non-sleep specialist providers. The goal of the study was to understand the impact of sleep consultation on PAP adherence. Methods Direct referral (DR) patients underwent polysomnography (PSG) and received PAP devices prior to the sleep clinic visit. In contrast, sleep center patients (SC) had a sleep clinic visit with a sleep physician or APRN prior to PSG. Eighty-four patients were included in this study, 42 DR and 42 SC patients. Exclusion criteria were age <18 years old, absence of baseline PSG, and lack of 90-day compliance data. Covariates included demographics, body mass index (BMI), AHI, nadir oxygen saturation, demographics, and Epworth Sleepiness Scale (ESS) score. Objective PAP adherence for first 90 days was the primary outcome. Results Age (p=0.1), ESS (p=0.3), BMI (p=0.6), and AHI (p=0.9) were not significantly different between the groups. SC patients had greater PAP adherence (4.77 hours, 95%CI: 4.1 to 5.4) compared to DR patients (3.61 hours, 95%CI: 2.88 to 4.33, p=0.02). SC patients were also 8 times more likely to follow up in clinic within 1 year of starting PAP treatment (Likelihood Ratio 8.25, p=0.004). Conclusion While possibly more time-efficient for patients, direct referrals may ultimately result in lower PAP adherence due to missed opportunities for receiving education about OSA and PAP therapy. This is consistent with findings from a previous meta-analysis demonstrating that educational interventions improve PAP adherence. Moving forward, we will continue encouraging directly referred patients to follow up in the sleep center after PSG. Support None

How Does Narcolepsy Impact Health-Related Quality of Life? A Mixed-Methods Study

ABSTRACT Study Objectives: The purpose of this study was to identify patient-centered issues affecting Health-Related Quality of Life (HRQoL) in people with narcolepsy (PWN) and to evaluate patient-reported outcome measures using a mixed-methods approach. Methods: Twenty-nine adults (93% female, mean age = 31 years) with an established diagnosis of narcolepsy (Type I = 58.6%) completed focus group interviews using live videoconferencing. Additionally, participants completed the Patient-Reported Outcomes Measurement Information System (PROMIS) measures along with legacy measures commonly used in narcolepsy research (Epworth Sleepiness Scale, Patient Health Questionnaire, Short-Form 36). Results: Thematic analysis of qualitative data revealed that HRQoL was impacted by the constancy of sleepiness, unpredictability of narcolepsy symptoms, and negative public perception of narcolepsy. Challenges to accessibility and/or quality of care included dissatisfaction with non-sleep specialists’ understanding of narcolepsy, the unpredictability of symptoms, and the cost of health care. There was enthusiasm for developing a psychosocial intervention to improve HRQoL using online access, but there were mixed opinions regarding the format, provider background, and content of the intervention. Elevations (T-score > 60) were found on PROMIS measures of depression, anxiety, fatigue, and sleep impairment. These patterns were consistent with the levels reported on legacy measures. PWN Type I reported lower levels of general health relative to Type II (p < .05). Conclusions: These findings lay the groundwork for more targeted efforts to address areas of diminished HRQoL in PWN. Additionally, PROMIS measures appear to be suitable and efficient instruments for assessing HRQoL in PWN.

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample.

Study ObjectivesPolysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction model to identify patients with high probability of OSA for nonsleep specialist physician in clinical practice.MethodsThe SVM model was developed using the features routinely collected at the clinical evaluation from 6,875 Chinese patients referred to sleep clinics for suspected OSA. Three apnea-hypopnea index (AHI) cutoffs, ≥5/h, ≥15/h, and ≥30/h were used to define the severity of OSA. The continuous and categorized features were selected separately and were further selected through stepwise forward feature selection. The modeling was achieved through fivefold cross-validation. The model discriminative ability was evaluated for the whole data set and four subgroups categorized with gender and age (<65 versus ≥65 years old [y/o]).ResultsTwo features were selected to predict AHI cutoff ≥5/h with six features selected for ≥15/h, and six features selected for ≥30/h, respectively, to reach Area under the Receiver Operating Characteristic (AUROC) 0.82, 0.80, and 0.78, respectively. The sensitivity was 74.14%, 75.18%, and 70.26%, while the specificity was 74.71%, 68.73%, and 70.30%, respectively. Compared to logistic regression, Berlin questionnaire, NoSAS Score, and Supersparse Linear Integer Model (SLIM) scoring system, the SVM model performs better with a more balanced sensitivity and specificity. The discriminative ability was best for male <65 y/o and modest for female ≥65 y/o.ConclusionOur model provides a simple and accurate modality for early identification of patients with OSA and may potentially help prioritize them for sleep study.

0634 Factors Influencing Best Practices in Narcolepsy: Results from a Predictive Modeling Analysis of Educational Outcomes Data

A continuing medical education (CME) activity was developed to improve knowledge and practice behaviors in healthcare providers (HCPs) treating patients with narcolepsy. The goal of this study was to utilize predictive modeling on educational outcomes data to determine factors influencing best practice behaviors so that any barriers may be addressed in future educational activities. Educational outcomes data were obtained from an activity on narcolepsy, which involved a 3-part webcast. Surveys assessing knowledge, confidence, and behavior were administered before and immediately following the activity. Two analyses using PredictCME (based on a method known as chi-square automatic interaction detection) were conducted on data from the pre-activity survey, which included questions related to practice behaviors; one question asked how often HCPs utilized a screening tool and one asked how often HCPs utilized diagnostic recommendations from the American Academy of Sleep Medicine (AASM). Data from each behavior question were used as the response variable in the 2 separate analyses. Demographics, knowledge, confidence, and evaluation data were entered as predictors. Data from 601 pre-survey participants were available for the analysis. Findings revealed specialty to be the strongest predictor of screening and diagnostic behaviors (X2(1) = 139.15, p < .001 and X2(1) = 40.42, p < .001, respectively), with sleep specialists more likely to perform these behaviors compared to non-sleep specialists. Results from the PredictCME analysis are not surprising in that sleep specialists are often directly involved in addressing sleep issues in patients. However, one could argue for the importance of non-sleep specialists utilizing screening tools, as that would help determine whether or not a referral to a sleep specialist is needed. Further, although a greater percentage of sleep specialists versus non-sleep specialists utilized diagnostic recommendations, only half of them did so. Therefore future educational activities should emphasize the importance of screening tools for non-sleep specialists, as well as diagnostic recommendations for both sleep and non-sleep specialists. The educational activity described in this presentation was supported by an educational grant from Jazz Pharmaceuticals.

Provider Types and Outcomes in Obstructive Sleep Apnea Case Finding and Treatment: A Systematic Review.

Obstructive sleep apnea (OSA) diagnosis and care models rely on sleep specialist physicians (SSPs) and can be expensive and inefficient. To assess OSA case-finding accuracy and comparative effectiveness of care by non-sleep specialists (NSSs) and SSPs. MEDLINE and CINAHL from January 2000 through July 2017. English-language trials or observational studies comparing case finding or care by SSPs versus providers not specifically trained as SSPs (NSSs) for adults with suspected or diagnosed OSA. One investigator extracted data and assessed risk of bias and strength of evidence, with confirmation by a second investigator. Primary outcomes were patient-centered (mortality, access to care, quality of life, patient satisfaction, adherence, symptom scores, and adverse events). Intermediate outcomes included resource use, costs, time to initiation of treatment, and case finding. Four observational studies (n= 580; mean age, 52 years; 77% male) reported good agreement between NSSs and SSPs on appropriate diagnostic testing and classification of OSA severity (low-strength evidence). Five randomized trials and 3 observational studies (n= 1515; mean age, 52 years; 68% male) found that care provided by NSSs and SSPs resulted in similar quality of life, adherence, and symptom scores (low-strength evidence). Evidence was insufficient for access to care and adverse events. Many outcomes were reported infrequently or not at all. Many NSSs had extensive training or experience in sleep medicine, which limits generalizability of findings to providers with less experience. Care by NSSs and SSPs resulted in similar outcomes in adults with known or suspected OSA. Studies are needed to determine care model implementation and reproducibility of results in nonacademic settings and among less experienced NSSs. Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Quality Enhancement Research Initiative. (PROSPERO: CRD42016036810 [full Veterans Affairs Evidence-based Synthesis Program report]).

A brief tool to differentiate factors contributing to insomnia complaints.

A complaint of insomnia may have many causes. A brief tool examining contributing factors may be useful for nonsleep specialists. This study describes the development of the Insomnia Symptoms Assessment (ISA) for examining insomnia complaints. ISA questions were designed to identify symptoms that may represent 1 of 8 possible factors contributing to insomnia symptoms, including delayed sleep phase syndrome (DSPS), shift work sleep disorder (SWSD), obstructive sleep apnea (OSA), mental health, chronic pain, restless leg syndrome (RLS), poor sleep hygiene, and psychophysiological insomnia (PI). The ISA was completed by 346 new patients. Patients met with a sleep specialist who determined primary and secondary diagnoses. Mean age was 45 (18-85) years and 51% were male. Exploratory factor analysis (n = 217) and confirmatory factor analysis (n = 129) supported 5 factors with good internal consistency (Cronbach's alpha), including RLS (.72), OSA (.60), SWSD (.67), DSPS (.64), and PI (.80). Thirty percent had 1 sleep diagnosis with a mean of 2.2 diagnoses per patient. No diagnosis was entered for 1.2% of patients. The receiver operating characteristics were examined and the area under the curves calculated as an indication of convergent validity for the primary diagnosis (N = 346) were .97 for SWSD, .78 for OSA, .67 for DSPS, .54 for PI, and .80 for RLS. The ISA demonstrated good internal consistency and corresponds well to expert diagnoses. Next steps include setting sensitivity/specificity cutoffs to suggest initial treatment recommendations for use in other settings. (PsycINFO Database Record

A clinician's guide to recurrent isolated sleep paralysis.

This review summarizes the empirical and clinical literature on sleep paralysis most relevant to practitioners. During episodes of sleep paralysis, the sufferer awakens to rapid eye movement sleep-based atonia combined with conscious awareness. This is usually a frightening event often accompanied by vivid, waking dreams (ie, hallucinations). When sleep paralysis occurs independently of narcolepsy and other medical conditions, it is termed “isolated” sleep paralysis. Although the more specific diagnostic syndrome of “recurrent isolated sleep paralysis” is a recognized sleep–wake disorder, it is not widely known to nonsleep specialists. This is likely due to the unusual nature of the condition, patient reluctance to disclose episodes for fear of embarrassment, and a lack of training during medical residencies and graduate education. In fact, a growing literature base has accrued on the prevalence, risk factors, and clinical impact of this condition, and a number of assessment instruments are currently available in both self-report and interview formats. After discussing these and providing suggestions for accurate diagnosis, differential diagnosis, and patient selection, the available treatment options are discussed. These consist of both pharmacological and psychotherapeutic interventions which, although promising, require more empirical support and larger, well-controlled trials.

Alcohol and Sleep Review: Sound Statistics and Valid Conclusions

HANK YOU FOR forwarding to us the letter fromPressman and colleagues (2015) and for inviting ourresponse.The role of alcohol and its impact on sleep has been stud-ied for more than a century, and a substantial knowledgebase has been created. The studies, like most scientific stud-ies, are dependent on the technology available at the timeandtheavailabilityofdata.Thisissomethingwetookintoconsiderationwhenprepar-ing our qualitative review on the impact of alcohol on nor-malsleep.Theissuesraisedcanbesummarizedasfollows:1. The use of percentages to represent the difference inthe mean values of sleep architecture variables in ourtables,2. Our results and conclusions as they pertain to the impactofalcohol onslowwavesleep(SWS),3. Ourinclusion–exclusioncriteriaforstudies,and4. Alcohol, N3, sleepwalking, and medico-legal conse-quences.1. The use of the mean value as a percentage to representsleeparchitecturevariables:1.1. In our article, we made clear how we have presentedthedata:Valuesforsleep architecturevariablesareprovidedinper-centage terms only. Where the researchers have reportedsleep stage data in minutes we have converted these intopercentages. Some variables, such as sleep onset latencyand rapid eye movement onset latency are reported inminutes only. Only the mean value is displayed for allvariables in the tables to enable a uniform approachthroughout(Ebrahimet al.,2013).1.2. This was accepted by the Journal and the peerreviewers as this review was based on highlighting 2specificareas:1.2.1. The impact of various alcohol doses and their tim-ing on nocturnal sleep in healthy controls and nor-mal populations.1.2.2. The impact of these alcohol doses on various sleepstages.1.3. Asthis was a qualitative reviewand not a quantitativemeta-analysis, it was our aim to provide a broadunderstanding to the “nonsleep specialist”readershipoftheimpactofalcoholonsleep.1.4. Furthermore, in routine clinical practice, sleepstages are reported both in actual time and as apercentage of total sleep, a simple difference in themeans between alcohol and placebo nights wasthought to be the best way to demonstrate theeffect.2. Alcohol andSWS:2.1. Alcohol andfirsthalfofnightSWS(N3):2.1.1. Low dose alcohol studies—Of the 4 studiesreported, 2 showed a significant increase in SWS(MacLean and Cairns, 1982; Van Reen et al., 2011)and the other 2 studies failed to find a significantdifference;2.1.2. Moderatedose studies—Ofthe 5 studies reported,2studies demonstrated a significant increase in SWS(Roehrs et al., 1999; Williams et al., 1983). Theother3 studiesfailedtodemonstrateany significantfindings;2.1.3. High dose studies—Five of the 9 studies reported astatistically significant increase in SWS with alco-hol (Arnedt et al., 2011; Feige et al., 2006;MacLean and Cairns, 1982; Prinz et al., 1980; Wil-liams et al., 1983) and 4 studies did not show anysignificantdifferences.The direction of evidence confirms that at low and moder-ate doses alcohol is not clearly associated with increased

CPAP Adherence during the Perioperative Period

CPAP Adherence during the Perioperative Period

A Brief Survey of Patients' First Impression after CPAP Titration Predicts Future CPAP Adherence: A Pilot Study

CPAP adherence patterns are often established very early in the course of therapy. Our objective was to quantify patients' perception of CPAP therapy using a 6-item questionnaire administered in the morning following CPAP titration. We hypothesized that questionnaire responses would independently predict CPAP adherence during the first 30 days of therapy. We retrospectively reviewed the CPAP perception questionnaires of 403 CPAP-naïve adults who underwent in-laboratory titration and who had daily CPAP adherence data available for the first 30 days of therapy. Responses to the CPAP perception questionnaire were analyzed for their association with mean CPAP adherence and with changes in daily CPAP adherence over 30 days. Patients were aged 52 ± 14 years, 53% were women, 54% were African American, the mean body mass index (BMI) was 36.3 ± 9.1 kg/m(2), and most patients had moderate-severe OSA. Four of 6 items from the CPAP perception questionnaire- regarding difficulty tolerating CPAP, discomfort with CPAP pressure, likelihood of wearing CPAP, and perceived health benefit-were significantly correlated with mean 30-day CPAP adherence, and a composite score from these 4 questions was found to be internally consistent. Stepwise linear regression modeling demonstrated that 3 variables were significant and independent predictors of reduced mean CPAP adherence: worse score on the 4-item questionnaire, African American race, and non-sleep specialist ordering polysomnogram and CPAP therapy. Furthermore, a worse score on the 4-item CPAP perception questionnaire was consistently associated with decreased mean daily CPAP adherence over the first 30 days of therapy. In this pilot study, responses to a 4-item CPAP perception questionnaire administered to patients immediately following CPAP titration independently predicted mean CPAP adherence during the first 30 days. Further prospective validation of this questionnaire in different patient populations is warranted.

Dissemination of CBTI to the Non-Sleep Specialist: Protocol Development and Training Issues

Strong evidence supports the efficacy of cognitive behavioral therapy for insomnia (CBTI). A significant barrier to wide dissemination of CBTI is the lack of qualified practitioners. We describe challenges and decisions made when developing a CBTI dissemination program in the Veterans Health Administration (VHA). The program targets mental health clinicians from different disciplines (psychiatry, psychology, social work, and nursing) with varying familiarity and experience with general principles of cognitive behavioral therapies (CBT). We explain the scope of training (how much to teach about the science of sleep, comorbid sleep disorders, other medical and mental health comorbidities, and hypnotic-dependent insomnia), discuss adaptation of CBTI to address the unique challenges posed by comorbid insomnia, and describe decisions made about the strategy of training (principles, structure and materials developed/recommended). Among these decisions is the question of how to balance the structure and flexibility of the treatment protocol. We developed a case conceptualization-driven approach and provide a general session-by-session outline. Training licensed therapists who already have many professional obligations required that the training be completed in a relatively short time with minimal disruptions to training participants' routine work responsibilities. These "real-life" constraints shaped the development of this competency-based, yet pragmatic training program. We conclude with a description of preliminary lessons learned from the initial wave of training and propose future directions for research and dissemination.

The Impact of Sleep Consultation Prior to a Diagnostic Polysomnogram on Continuous Positive Airway Pressure Adherence

Polysomnograms (PSGs) are routinely ordered by nonsleep specialists. However, it is unknown whether a sleep specialist consultation prior to a diagnostic PSG influences adherence to continuous positive airway pressure (CPAP) therapy. This study was done at the University of Chicago Sleep Disorders Center and included 403 patients with obstructive sleep apnea who had CPAP adherence data available. CPAP was set up at home, and objective adherence was remotely monitored during the first 30 days of therapy. Physicians who ordered PSGs were divided into two groups: sleep specialists and nonsleep specialists. Patients were aged 52.5 ± 14 years, 47% were men, and 54% were African American. Mean daily CPAP use was greater in patients who were referred by sleep specialists (n = 105, 279 ± 179 min/d) than in patients referred by nonsleep specialists (n = 298, 219 ± 152 min/d, P = .005). In the linear regression model adjusting for several covariates, only two predictors were significantly associated with CPAP adherence. A sleep specialist consultation prior to the diagnostic PSG was associated with 58.2 min more per day (P = .002), and African American race was associated with 56.0 min less per day (P = .002) of CPAP use. In this cohort study, CPAP adherence was significantly higher with a sleep specialist consultation prior to the diagnostic PSG. In addition, African American race was associated with worse adherence to therapy. A better understanding of predictors of CPAP adherence may be useful in identifying patients who may benefit from a sleep specialist consultation prior to ordering a diagnostic PSG.

Approach to the Patient with Sleep Complaints

Sleep disorders are both common and consequential, but too often remain undiagnosed. The insidious, chronic course of most sleep disorders and lack of patient awareness of signs and symptoms during sleep can complicate the clinical evaluation. Typical chief complaints include snoring, excessive daytime sleepiness, insomnia, and behaviors during sleep. Sleep disorders can be primary or secondary to medical, neurologic, or psychiatric conditions, so a multidisciplinary approach is often desirable. Family members can be a critical source of information as they may have observed nocturnal or daytime symptoms unrecognized by the patient. Objective testing plays an important role in assessment for obstructive sleep apnea, parasomnias, and other specific sleep disorders, and can be used most effectively in combination with a thorough clinical evaluation. Nonsleep specialists should consider obtaining assistance from sleep clinicians for more challenging presentations or management of sleep disorders unfamiliar to them.

CLINICIAN'S GUIDE TO SLEEP DISORDERS

CLINICIAN'S GUIDE TO SLEEP DISORDERS edited by Nathaniel F. Watson and Bradley V. Vaughn , 416 pp., Taylor & Francis, 2006, $199.95 Drs. Watson and Vaughn's Clinician's Guide to Sleep Disorders was written with the purpose of facilitating “primary care providers and non-sleep medicine specialists as they care for patients with sleep complaints.” By providing a symptom-based, table-friendly text, the authors wrote the book to be used as a quick …