Sleep Specialists Research Articles

Sleep-disordered breathing diagnosis: a comprehensive audit of home sleep testing in real clinical settings.

This study aimed to investigate the indications and outcomes of Home Sleep Testing (HST) for patients with suspected obstructive sleep apnea (OSA), aligning with guidelines set forth by the American Academy of Sleep Medicine and the European Sleep Research Society. Specifically, we aimed to audit whether validated type 3 polygraphy could effectively ensure patient care while optimizing resource utilization. A retrospective analysis was conducted on data from patients undergoing type 3 polygraphy for suspected OSA in a tertiary referral hospital between January 2022 and December 2022. Demographic, clinical, and management data were collected. The efficacy of HST in guiding management plans was evaluated, with outcomes categorized as effective or ineffective based on subsequent need for in-laboratory polysomnography. While 85% of patients received a reliable diagnosis, 44.4% of them still required subsequent polysomnography, primarily due to adherence to funding regulations, rather than clinical need for further testing. Factors impacting the efficacy of HST included patient age, severity of apnea, and referral by a certified sleep specialist physician. Our study highlighted the potential of type 3 polygraphy, as a valuable tool for diagnosing OSA in an outpatient setting. However, having the result interpreted by a certified sleep specialist doctor was not enough. To streamline the care pathway, the referral for polygraphy had also to be made by a trained specialist. Challenges related to funding regulations, patient demographics and physician training stress the need for optimized diagnostic pathways to improve patient care and resource utilization.

History of symptoms consistent with REM sleep behavior disorder in a population with Parkinson's Disease

REM Sleep Behavioral Disorder (RBD) is a parasomnia marked by the maintenance of muscle tone during REM sleep. Evidence has placed RBD as one of the possible prodromal stages of Parkinson's Disease (PD), but data on the proportion of people with PD who have had symptoms of RBD are limited. This study aimed to investigate the history of symptoms compatible with RBD in a population with PD. The sample was composed by 73 patients with clinically diagnosed PD being followed up at a reference outpatient setting, compared to 73 age- and sex-matched individuals with no PD. The evaluation of symptoms compatible with RBD was performed using the Brazilian version of the RBD Screening Questionnaire (RBDSQ). The prevalence of symptoms compatible with RBD was 65 % for PD and 10.09 % for controls. The RBDSQ score was significantly higher in the PD group (6.03 ± 0.35) in comparison to the control group (2.38 ± 0.23). The odds ratio for presenting previous RBD-compatible symptoms was 12.09 in favor of positive PD cases. PD diagnosis has the following diagnostic properties in relation to presenting RBD symptoms: sensitivity of 0.65, specificity of 0.86, positive predictive value of 0.82 and negative predictive value of 0.71. In conclusion, the proportion of PD patients showing RBD symptoms is high, corroborating the expected neuroprogression of the disease on a case-control design comprising outpatient PD cases. Clinical practitioners should include evaluations of RBD-compatible symptoms during the PD assessment and, if positive, forward to a sleep specialist.

Construction of an index system of core competence assessment for sleep medicine nurse specialists in China: a Delphi study

AimTo construct an evaluation index system for the core competence of nurses in sleep medicine specialties.BackgroundSpecialized nurses in sleep medicine must handle treatment, nursing, and management well, which requires nurses to have excellent competence in knowledge, skills, and ability. However, a competency evaluation system for sleep medicine nurses has not been established in China.MethodsWe used a literature review and an expert meeting to establish a draft indicator system. Subsequently, two rounds of correspondence were conducted with 27 experts from 5 provinces using the Delphi method to solicit their opinions on the core competency evaluation indicators for sleep medicine nurse specialists and to qualitatively evaluate the experts’ scores. The consensus was defined in advance as a mean score of 4.0 or above, with at least 75% agreement among participants. In this way, the final indicator framework was determined.ResultsThe final evaluation indexes of the core competencies for sleep medicine Nurse Specialists included 6 first-level indexes (Practical ability, Theoretical Knowledge, Critical thinking, Communication and coordination, Nursing Management, and Professional Development), 16 s-level indexes, and 64 third-level indexes. The effective response rates of the two expert consultation rounds were 100%. The expert authority coefficients were 0.878 and 0.865 in the first and second rounds of consultation, respectively. In the second round of consultation, the first, second, and third indexes of Kendall’s coefficient of concordance were 0.373, 0.351, and 0.286, respectively (P < 0.05).ConclusionThe core competence evaluation index system for sleep medicine nurses established in this study is scientific and reliable and can provide a theoretical reference for the training, assessment, and evaluation of sleep medicine nurses in the future.Implications for nursing managementThe evaluation index system of sleep medicine nurses’ core competence will provide an effective practical framework for nursing management to evaluate, train, and examine the core competence of sleep medicine nurses.

International expert consensus statement: surgical failure in obstructive sleep apnea.

Upper airway (UA) surgery is commonly employed in the treatment of patients with obstructive sleep apnea (OSA). The intricate pathophysiology of OSA, variability in sites and patterns of UA collapse, and the interaction between anatomical and non-anatomical factors in individual patients may contribute to possible surgical failures. This clinical consensus statement aims to identify areas of agreement among a development group comprising international experts in OSA surgery, regarding the appropriate definition, predictive factors in patients, and management of surgical failure in OSA treatment. A clinical consensus statement (CCS) was developed using the Delphi method by a panel of 35 contributors from various countries. A systematic literature review adhering to PRISMA guidelines was conducted. A survey consisting of 60 statements was then formulated and presented to the experts. Following two rounds of the Delphi process, consensus or strong consensus was achieved on 36 items, while 24 items remained without consensus. Specifically, 5 out of 10 statements reached consensus regarding on the 'Definition of Surgical Success/Failure after OSA Surgery'. Regarding the 'Predictive Factors of Surgical Failure in OSA Surgery', consensus was reached on 10 out of 13 statements. In the context of the 'Diagnostic Workup in OSA Surgery', consensus was achieved on 9 out of 13 statements. Lastly, in 'Treatment in Surgical Failure Cases', consensus was reached on 12 out of 24 statements. The management of OSA after surgical failure presents a significant clinical challenge for sleep specialists. This CCS provides valuable guidance for defining, preventing, and addressing surgical failures in the treatment of OSA syndrome.

Knowledge and Attitude of General Dentists, Senior Dental Students, and Orthodontic Residents Toward Obstructive Sleep Apnea.

The main objective of this study was to compare the knowledge and attitude of general dentists, senior dental students, and orthodontic residents toward obstructive sleep apnea (OSA). A questionnaire was designed and administered among 73 senior dental students, 84 general dentists, and 50 orthodontic residents. The questionnaire asked for demographic information of the participants and assessed their knowledge and attitude toward OSA. The validity and reliability of the questionnaire were confirmed by experts. Data were analyzed by the Kruskal-Wallis and Bonferroni tests using SPSS (α = 0.05). The mean knowledge scores of general dentists and senior dental students were significantly lower than those of orthodontic residents (p < 0.001). However, there was no significant difference in the knowledge score of senior dental students and general dentists (p = 1). The mean knowledge score was significantly higher in dentists with 1-3 years of professional clinical experience (p = 0.02). The knowledge score was the highest in dentists working in private clinics followed by private offices and public clinics. The mean attitude score was the highest in orthodontic residents followed by general dentists and dental students. There was no significant difference in attitude based on the attended university, age, or time of graduation. According to the results, general dentists had insufficient knowledge about OSA, which could result in under-diagnosis or misdiagnosis of patients with OSA. This finding highlights the need for further education and training for dentists to properly identify and refer OSA patients to orthodontists or sleep specialists.

ChatGPT vs. sleep disorder specialist responses to common sleep queries: Ratings by experts and laypeople

BackgroundMany individuals use the Internet, including generative artificial intelligence like ChatGPT, for sleep-related information before consulting medical professionals. This study compared responses from sleep disorder specialists and ChatGPT to common sleep queries, with experts and laypersons evaluating the responses' accuracy and clarity. MethodsWe assessed responses from sleep medicine specialists and ChatGPT-4 to 140 sleep-related questions from the Korean Sleep Research Society's website. In a blinded study design, sleep disorder experts and laypersons rated the medical helpfulness, emotional supportiveness, and sentence comprehensibility of the responses on a 1-5 scale. ResultsLaypersons rated ChatGPT higher for medical helpfulness (3.79 ± 0.90 vs. 3.44 ± 0.99, p < .001), emotional supportiveness (3.48 ± 0.79 vs. 3.12 ± 0.98, p < .001), and sentence comprehensibility (4.24 ± 0.79 vs. 4.14 ± 0.96, p = .028). Experts also rated ChatGPT higher for emotional supportiveness (3.33 ± 0.62 vs. 3.01 ± 0.67, p < .001) but preferred specialists' responses for sentence comprehensibility (4.15 ± 0.74 vs. 3.94 ± 0.90, p < .001). When it comes to medical helpfulness, the experts rated the specialists' answers slightly higher than the laypersons did (3.70 ± 0.84 vs. 3.63 ± 0.87, p = .109). Experts slightly preferred specialist responses overall (56.0%), while laypersons favored ChatGPT (54.3%; p < .001). ChatGPT's responses were significantly longer (186.76 ± 39.04 vs. 113.16 ± 95.77 words, p < .001). DiscussionGenerative artificial intelligence like ChatGPT may help disseminate sleep-related medical information online. Laypersons appear to prefer ChatGPT's detailed, emotionally supportive responses over those from sleep disorder specialists.

Co-morbid Insomnia and Sleep Apnea (COMISA) in a large sample of Iranian: prevalence and associations in a sleep clinic population.

Sleep apnea (SA) and insomnia (INS) are prevalent sleep disorders among referrals to sleep clinics. People with comorbid insomnia and sleep apnea (COMISA) suffer both disorders simultaneously. The epidemiology of COMISA is not well known in the Middle East including Iran. We hypothesized that COMISA is prevalent in metropolitan sleep clinic cohorts in Iran. The records of patients aged < 95 years referred to sleep disorders centers in four large metropolitan areas including Kermanshah, Tabriz, Shiraz, and Ahvaz were examined. Polysomnography (PSG) was performed in all these patients in specialized centers and the results were scored by a trained technician and interpreted by a sleep specialist. SA was defined as an Apnea-Hypopnea Index (AHI ≥ 5), INS was defined by psychiatrists according to self-report and clinical interviews, and COMISA was defined if both disorders were present. Participants with neither condition were included in as comparator group. One-way ANOVAs, correlation, and linear/logistic regression analyses were used. This study included 1807 patients (Mean age 49.3, SE ± 13.7; 38.8% Female). Comparator, INS, SA and COMISA made up 7.2%, 16%, 50.2% and 26.6% of the sample, respectively. Logistic regression analyses showed that male gender, older age, and increasing neck circumference, but not BMI, were associated with COMISA. Epworth Sleepiness Scale scores were lower in INS (5.39 ± 5.78) compared to the other three groups. COMISA is a prevalent condition in metropolitan sleep centers in Iran among participants referred to sleep centers. The data showed that male gender and age were associated significantly with COMISA.

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enhancing reliability by identifying regions of heightened and diminished confidence. In this study, we used an uncertainty-centred machine learning pipeline, U-PASS, to automate sleep staging in a challenging real-world dataset of single-channel electroencephalography and accelerometry collected with a wearable device from an elderly population. We were able to effectively limit the uncertainty of our machine learning model and to reliably inform clinical experts of which predictions were uncertain to improve the machine learning model's reliability. This increased the five-stage sleep-scoring accuracy of a state-of-the-art machine learning model from 63.9% to 71.2% on our dataset. Remarkably, the machine learning approach outperformed the human expert in interpreting these wearable data. Manual review by sleep specialists, without specific training for sleep staging on wearable electroencephalography, proved ineffective. The clinical utility of this automated remote monitoring system was also demonstrated, establishing a strong correlation between the predicted sleep parameters and the reference polysomnography parameters, and reproducing known correlations with the apnea-hypopnea index. In essence, this work presents a promising avenue to revolutionize remote patient care through the power of machine learning by the use of an automated data-processing pipeline enhanced with uncertainty estimation.

Impact of Continuous Positive Airway Pressure Termination on Permanent Work Disability in Obstructive Sleep Apnea: A French Nationwide ALASKA Database Analysis.

Rationale: Three-year continuous positive airway pressure (CPAP) therapy termination rates are up to 50%, and therapy termination is associated with higher all-cause mortality and incident cardiovascular event risk. Objectives: This study investigated the impact of CPAP therapy termination in the first year on long sick leave leading to permanent work disability in patients with obstructive sleep apnea based on data from the Nationwide Claims Data Lake for Sleep Apnoea (ALASKA). Methods: French national health insurance reimbursement system data were analyzed for all adults with OSA aged ≤62 years who started CPAP therapy in France in 2015 and 2016. CPAP therapy termination was defined as the cessation of CPAP reimbursements triggered by the respiratory physician or sleep specialist in charge of follow-up. Individuals who terminated therapy were compared with those who continued to use CPAP. The primary outcome was sick leave ultimately leading to permanent work disability. A multivariable Fine and Gray model, adjusted for age, sex, cardiovascular and metabolic comorbidities, depression, and CPAP prescriber clinical specialty was used to assess the risk of long-term sick leave leading to permanent work disability over 3 years' follow-up. Results: The analysis included 174,270 individuals (median age, 52.0 yr [interquartile range, 44.0-57.0 yr]; 67.5% male). The 1-year CPAP therapy termination rate was 22.3%. The proportion of individuals with long-term sick leave leading to permanent work disability was significantly higher in the CPAP termination versus continuation group (0.60% vs. 0.52%; P = 0.042). In an adjusted multivariable Cox model, CPAP termination was associated with an increased risk of permanent work disability (hazard ratio, 1.21; 95% confidence interval [CI], 1.04-1.41; P = 0.01), primarily in the subgroup aged >55 years (hazard ratio, 1.41; 95% CI, 1.06-1.87; P = 0.02). Conclusions: These real-world data from a comprehensive, unbiased database highlight the potential occupational impact of CPAP therapy termination.

Zolpidem-triggered atrial fibrillation in a patient with cardiomyopathy: a case report

BackgroundZolpidem is a non-benzodiazepine hypnotic widely used to manage insomnia. Zolpidem-triggered atrial fibrillation (AF) in patients with cardiomyopathy has never been reported before.Case presentationA 40-year-old man with Duchenne muscular dystrophy-related cardiomyopathy attempted suicide and developed new-onset AF after zolpidem overdose. One year before admission, the patient visited our clinic due to chest discomfort and fatigue after daily walks for 1 month; both electrocardiography (ECG) and 24-hour Holter ECG results did not detect AF. After administration of cardiac medication (digoxin 0.125 mg/day, spironolactone 40 mg/day, furosemide 20 mg/day, bisoprolol 5 mg/day, sacubitril/valsartan 12/13 mg/day), he felt better. AF had never been observed before this admission via continuous monitoring during follow-up. Sixteen days before admission, the patient saw a sleep specialist and started zolpidem tartrate tablets (10 mg/day) due to insomnia for 6 months; ECG results revealed no significant change. The night before admission, the patient attempted suicide by overdosing on 40 mg of zolpidem after an argument, which resulted in severe lethargy. Upon admission, his ECG revealed new-onset AF, necessitating immediate cessation of zolpidem. Nine hours into admission, AF spontaneously terminated into normal sinus rhythm. Results from the ECG on the following days and the 24-hour Holter ECG at 1-month follow-up showed that AF was not detected.ConclusionsThis study provides valuable clinical evidence indicating that zolpidem overdose may induce AF in patients with cardiomyopathy. It serves as a critical warning for clinicians when prescribing zolpidem, particularly for patients with existing heart conditions. Further large-scale studies are needed to validate this finding and to explore the mechanisms between zolpidem and AF.

Evaluation of Sleep Quality in Asthmatic Children with the Paediatric Sleep Questionnaire (PSQ).

Considering the high prevalence of sleep-related breathing disorders (SRBD) in asthmatic patients, we aimed to compare asthmatic children and healthy children in terms of SRBD according to Paediatric Sleep Questionnaire (PSQ) scores. A questionnaire covering sociodemographic characteristics of the patients and the PSQ, which evaluates sleep quality and consists of 22 questions, was administered. During the data collection process, 180 patients in the patient group and 170 patients in the control group were included. The patient group showed statistically significantly higher total scores and subscale scores for snoring, sleepiness, and inattention compared to the control group. Statistically significant correlations were found between the sleepiness subscale and body mass index z score in a negative direction and between age at presentation and duration of asthma in a positive direction. Our findings endorse employing the PSQ as a screening instrument in the outpatient environment to ensure timely referral of asthma patients to a sleep specialist for SRBD evaluation. Considering the widespread occurrence of snoring and asthma, this tool could aid in identifying patients with an elevated risk of SRBD and expedite the scheduling of nocturnal polysomnography for these children.

MVF-SleepNet: Multi-View Fusion Network for Sleep Stage Classification.

Sleep stage classification is of great importance in human health monitoring and disease diagnosing. Clinically, visual-inspected classifying sleep into different stages is quite time consuming and highly relies on the expertise of sleep specialists. Many automated models for sleep stage classification have been proposed in previous studies but their performances still exist a gap to the real clinical application. In this work, we propose a novel multi-view fusion network named MVF-SleepNet based on multi-modal physiological signals of electroencephalography (EEG), electrocardiography (ECG), electrooculography (EOG), and electromyography (EMG). To capture the relationship representation among multi-modal physiological signals, we construct two views of Time-frequency images (TF images) and Graph-learned graphs (GL graphs). To learn the spectral-temporal representation from sequentially timed TF images, the combination of VGG-16 and GRU networks is utilized. To learn the spatial-temporal representation from sequentially timed GL graphs, the combination of Chebyshev graph convolution and temporal convolution networks is employed. Fusing the spectral-temporal representation and spatial-temporal representation can further boost the performance of sleep stage classification. A large number of experiment results on the publicly available datasets of ISRUC-S1 and ISRUC-S3 show that the MVF-SleepNet achieves overall accuracy of 0.821, F1 score of 0.802 and Kappa of 0.768 on ISRUC-S1 dataset, and accuracy of 0.841, F1 score of 0.828 and Kappa of 0.795 on ISRUC-S3 dataset. The MVF-SleepNet achieves competitive results on both datasets of ISRUC-S1 and ISRUC-S3 for sleep stage classification compared to the state-of-the-art baselines. The source code of MVF-SleepNet is available on Github (https://github.com/YJPai65/MVF-SleepNet).

Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?

Paediatric sleep diagnostics is performed using complex multichannel tests in specialised centres, limiting access and availability and resulting in delayed diagnosis and management. Such investigations are often challenging due to patient size (prematurity), tolerability, and compliance with "gold standard" equipment. Children with sensory/behavioural issues, at increased risk of sleep disordered breathing (SDB), often find standard diagnostic equipment difficult.SDB can have implications for a child both in terms of physical health and neurocognitive development. Potential sequelae of untreated SDB includes failure to thrive, cardiopulmonary disease, impaired learning and behavioural issues. Prompt and accurate diagnosis of SDB is important to facilitate early intervention and improve outcomes.The current gold-standard diagnostic test for SDB is polysomnography (PSG), which is expensive, requiring the interpretation of a highly specialised physiologist. PSG is not feasible in low-income countries or outwith specialist sleep centres. During the coronavirus disease 2019 pandemic, efforts were made to improve remote monitoring and diagnostics in paediatric sleep medicine, resulting in a paradigm shift in SDB technology with a focus on automated diagnosis harnessing artificial intelligence (AI). AI enables interrogation of large datasets, setting the scene for an era of "sleep-omics", characterising the endotypic and phenotypic bedrock of SDB by drawing on genetic, lifestyle and demographic information. The National Institute for Health and Care Excellence recently announced a programme for the development of automated home-testing devices for SDB. Scorer-independent scalable diagnostic approaches for paediatric SDB have potential to improve diagnostic accuracy, accessibility and patient tolerability; reduce health inequalities; and yield downstream economic and environmental benefits.

Dosing Optimization of Low-Sodium Oxybate in Narcolepsy and Idiopathic Hypersomnia in Adults: Consensus Recommendations.

Low-sodium oxybate (LXB) is approved for treatment of narcolepsy in patients aged 7years and older and treatment of idiopathic hypersomnia in adults. LXB contains the same active moiety with 92% less sodium than sodium oxybate (SXB). As the indication for oxybate treatment in patients with idiopathic hypersomnia is new and allows for individualized dosing optimization, guidance for beginning LXB treatment is needed. In particular, clinicians may benefit from guidance regarding treatment initiation, dosing/regimen options, potential challenges, and treatment expectations. Additionally, pharmacokinetic profiles differ slightly between both treatments, and further guidance on transitioning from SXB to LXB in patients with narcolepsy may aid clinicians. An expert panel of five sleep specialists was convened to obtain consensus on recommendations for these topics using a modified Delphi process. Across two virtual meetings, the panel agreed on 31 recommendations with a high degree of consensus that fell into four overarching topics: (1) introducing LXB to patients; (2) initiating LXB for adult narcolepsy and idiopathic hypersomnia; (3) addressing challenges in using LXB; and (4) transitioning from SXB to LXB. The panel recommended that clinicians provide a clear overview of how LXB works for treating symptoms in narcolepsy or idiopathic hypersomnia, as appropriate for their patients, explain safety aspects, and set expectations prior to initiating LXB treatment. Strategies for initial dosing and regimen are provided. Strategies for adjusting the dose, regimen, timing, and consideration of individual factors were developed for specific instances in which patients may have trouble staying asleep or waking up, as well as guidance for addressing potential adverse events, such as nausea, dizziness, anxiety, and depression. Discussion points based on existing literature and clinical experience were included as relevant for each statement. Clinicians may use this resource to guide LXB dosing optimization with patients.

A survey-based approach on restless legs syndrome: practices and perspectives among Italian neurologists.

Restless Legs Syndrome (RLS) is a widely prevalent and complex neurological disorder. Despite notable advancements in managing RLS, the disorder continues to face challenges related to its recognition and management. This study seeks to gain comprehensive insights into the knowledge and clinical practices among Italian neurologists regarding RLS diagnosis, management, and treatment, comparing approaches among general neurologists, movement disorder specialists, and sleep experts. Members of the Italian Society of Neurology, the Italian Society of Parkinson and Movement Disorders, and the Italian Association of Sleep Medicine were invited to participate in a 19-question online survey. Among the 343 surveyed neurologists, 60% categorized RLS as a "sleep-related movement disorder." Forty% indicated managing 5-15 RLS patients annually, with sleep specialists handling the highest patient volume. Of note, only 34% adhered strictly to all five essential diagnostic criteria. The majority (69%) favored low-dosage dopamine agonists as their first-line treatment, with movement disorder specialists predominantly endorsing this approach, while sleep experts preferred iron supplementation. Regular screening for iron levels was widespread (91%), with supplementation typically guided by serum iron alterations. In cases of ineffective initial treatments, escalating dopamine agonist dosage was the preferred strategy (40%). These findings underscore a lack of a clear conceptualization of RLS, with a widespread misconception of the disorder as solely a movement disorder significantly influencing treatment approaches. Disparities in RLS understanding across neurology subspecialties underscore the necessity for improved diagnostic accuracy, targeted educational initiatives, and management guidelines to ensure consistent and effective RLS management.

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.

Workforce and Employment Status of Sleep Medicine Graduates in Iran

&#x0D; &#x0D; &#x0D; &#x0D; Background and Objective: Sleep medicine is a multidisciplinary specialty that focuses on diagnosing and treating sleep disorders. Sleep medicine fellowship programs in Iran commenced in 2012 at Tehran University of Medical Sciences, Tehran, Iran. This study aimed to investigate the human resources and employment status of sleep medicine fellowship graduates in Iran.&#x0D; Materials and Methods: This study was a descriptive cross-sectional study conducted in Iran in 2022 using conven- ience sampling and included 41 sleep medicine fellows in Iran. Data collection tools included a demographic question- naire and a researcher-made survey. Data were analyzed using the SPSS software.&#x0D; Results: Out of 57 sleep medicine fellows, 41 individuals with an average age of 44.95 ± 7.57 years participated in the study. Only 12% of the fellows were satisfied with their income, and all participants expressed dissatisfaction with their insurance coverage. 92% considered the existence of a national guideline for sleep medicine to be crucial, while 66.7% felt the curriculum of medical sleep medicine had some deficiencies.&#x0D; Conclusion: Lack of a suitable national guideline for treating and preventing sleep disorders, lack of insurance coverage for tests and respiratory assist devices, and high costs of establishing and equipping specialized sleep clinics are major challenges recognized by sleep medicine fellows. Additionally, due to the low priority given to these diseases by authorities and the inappropriate distribution of sleep medicine specialists in the country, access to appropriate treatment for sleep disorders is only feasible in giant cities.&#x0D; &#x0D; &#x0D; &#x0D;

Exploring the Intersection of Narcolepsy and Attention Deficit Hyperactivity Disorder: Similarities, Differences, and Clinical Implications

Narcolepsy and attention deficit hyperactivity disorder (ADHD) are distinct neurobiological conditions characterized by overlapping symptoms, including excessive daytime sleepiness and cognitive dysfunction. Despite their differences in etiology and pathophysiology, recent studies have highlighted a potential association between the two disorders, with a significant prevalence of ADHD symptoms observed in narcolepsy patients. This narrative review explores the similarities and differences between narcolepsy and ADHD, focusing on their shared symptomatology, neurobiological mechanisms, challenges in diagnosis, and treatment implications. While both disorders exhibit disruptions in dopaminergic and noradrenergic neurotransmitter systems, differential diagnosis remains challenging due to overlapping clinical presentations. Polysomnography findings, such as appearance of sleep onset rapid eye movements in narcolepsy patients, provide important distinctions that enable accurate diagnosis. Treatment strategies often involve stimulant medications for symptom management; however, nonpharmacological interventions, such as cognitive behavioral therapy, have been shown to have the potential to improve patient outcomes. Clinicians must consider the possibility of coexisting narcolepsy in ADHD patients and vice versa to ensure appropriate treatment selection and optimal patient care. Further research is needed to refine diagnostic criteria, elucidate the complex interplay between the two disorders, and develop personalized therapeutic approaches. A multidisciplinary approach involving sleep specialists, neurologists, psychiatrists, and psychologists is essential to address the diverse biopsychosocial needs of patients with concurrent narcolepsy and ADHD.

The Swiss Sleep House Bern—A New Approach to Sleep Medicine

Sleep is essential for health, well-being, creativity, and productivity. Sleep loss and sleep–wake circadian disorders (SWCDs) affect at least one in three individuals but are underdiagnosed and undertreated for different reasons: First, the importance of sleep health and, second, the burden of sleep loss and SWCDs are underestimated. Third, education in sleep medicine is insufficient and health care-related sleep research is underdeveloped. Fourth, the validation and implementation of tele-sleep medicine approaches and novel devices to monitor SWCDs are still insufficient. Fifth, the reimbursement of sleep medicine in most countries is inadequate and the availability of specialized care is limited to a few centers. The Swiss Sleep House Bern (SSHB) was founded in 2022 to address these challenges and eventually promote better care for patients with SWCDs and improve sleep health for the broader population. The interdisciplinary and interprofessional team of the SSHB, which is integrated in the Bernese Interdisciplinary Sleep-Wake-Epilepsy Center, links sleep specialists with primary care providers to offer a rapid and accessible triage and first-level management of sleep complaints and SWCDs. The SSHB also promotes awareness and offers educational programs on sleep health and SWCDs, performs health care research, and fosters the implementation of new technologies, data science, and telemedicine into clinical routine.

Multidisciplinary providers’ perceptions of care delivery for sleep disorders: A qualitative case study

ObjectivesSleep disorders are wide-ranging in their causes and impacts on other physical and mental health conditions. Thus, sleep disorders could benefit from a multidisciplinary approach to assessment and treatment. An integrated care model is often recommended but is costly to implement. We sought to understand how, in the absence of an established organizational structure for integrated sleep care, providers from different clinics work together to provide care for sleep disorders. MethodsA qualitative case study at one U.S. Department of Veterans Affairs (VA) medical center. We used a purposeful nested sampling strategy, combining maximum variation sampling and snowball sampling to recruit key staff involved in sleep care. ResultsWe interviewed providers (N = 10) from sleep medicine, primary care, and mental health services. Providers identified the ubiquity of sleep disorders and a concomitant need for multidisciplinary care. However, they described limited opportunities for multidisciplinary interactions and consequently a negative impact on clinical care. Providers described fragmentation in two areas: among sleep specialists and between sleep specialists and other referring and managing providers. ConclusionsA range of interventions, based on setting and resources, could improve care coordination both among sleep specialists and between sleep and nonsleep providers. While integrated sleep specialist clinics could reduce care fragmentation, they may not directly impact coordination with referring providers, like primary care and general mental health, who are essential in managing chronic conditions. Future work should continue to explore improving care coordination for sleep problems to ensure patients receive high-quality, timely, patient-centered care.