Journal of Clinical Sleep Medicine最新文献

Study objectives: The objective was to compare demographics between children with achondroplasia and OSA with the general pediatric population with OSA, as well as present treatment outcomes for children with achondroplasia.

Methods: Retrospective chart review of 22 children with achondroplasia and OSA and 141 children with OSA without achondroplasia. Parameters from polysomnography were analyzed. Values before and after surgery were compared for the achondroplasia group, while baseline values were compared between the control group and achondroplasia group.

Results: Pre-intervention in the T&A achondroplasia group, 0 children had mild OSA, 1 had moderate OSA, and 10 had severe OSA. In the comparative group 16 had mild OSA, 11 had moderate OSA, and 114 had severe OSA. The achondroplasia population had a much younger age at T&A compared to the control population - 3.1 versus 6.8 years. When comparing baseline data in the achondroplasia population with respective T&A outcomes, oAHI and SpO₂ were improved. For the adenoidectomy group, there were no significant changes in OSA after surgery. For the Cervicomedullary decompression (CMD) group, there was a decrease in oAHI after surgery.

Conclusions: Patients with achondroplasia and OSA have an earlier age of onset compared to children without achondroplasia. For these patients with moderate to severe OSA, treatment with adenotonsillectomy leads to significant improvement. Treatment with adenoidectomy showed no significant change in OSA. CMD also led to an improvement in oAHI.

Study objectives: This study aims to investigate the perception and interest of internal medicine (IM) residents in sleep medicine (SM). The focus is on understanding the current state of knowledge, training adequacy, and the inclination of residents towards pursuing sleep medicine subspecialty training.

Methods: We utilized the Indiana University Survey Questionnaire (IUSQ), a validated survey, to assess Internal Medicine residents' perceptions of sleep medicine. The anonymous digital survey was administered to residents at our ACGME-accredited internal medicine training program (IMTP).

Results: Of the 61 residents, 52 (85%) participated. The majority recognized the burden of sleep-disordered breathing (SDB) in the population and its importance for training and general practice. However, there was a notable discrepancy in their perception of receiving adequate training in SDB during residency. A significant proportion expressed a neutral stance or disagreement with the idea of pursuing sleep medicine fellowship, citing a lack of interest or comfort in managing sleep disorders.

Conclusions: Despite the rising prevalence of sleep-related breathing disorders, there exists a gap in residents' interest in specializing in sleep medicine. This underscores the need for improved sleep medicine education in residency programs. Bridging this educational gap requires curricular enhancements, increased clinical exposure, and mentorship in sleep medicine. Addressing these issues will better equip future physicians to meet the growing demands of sleep medicine and enhance overall patient care.

Study objectives: We propose to identify different sleep phenotypes in infancy, relying on auto-videosomnography metrics.

Methods: In this cross-sectional study, objective infant sleep metrics of six hundred twenty-three infants aged 9 to 13 months, recruited among users of Nanit baby-monitor in the United States, were obtained from Nanit auto-videosomnography (1 week of data averaged) in the child's natural sleep environment. A cluster analysis was conducted to group infants based on sleep metrics.

Results: Three reproducible and stable sleep phenotypes were identified: Long Sleepers (n.338), Interrupted Sleepers (n.130) and Short Sleepers (n.155). All sleep metrics were statistically significant different in the three groups. Long Sleepers had longer nighttime sleep duration than Interrupted and Short Sleepers. Interrupted Sleepers presented more awakenings than Short and Long Sleepers, and similarly more parental interventions. Short Sleepers presented later bedtimes and earlier wake up times when compared with Long and Interrupted Sleepers. Nighttime sleep efficiency was better in Long Sleepers than in Interrupted and Short Sleepers, but Short Sleepers presented better sleep efficiency than Interrupted Sleepers.

Conclusions: Cluster analysis based on objective sleep metrics offers a novel multidimensional approach for the early identification of infants' sleep patterns. Phenotyping sleep patterns is extremely important in identifying the risk for developing neurobehavioral disorders since night wakings and reduced sleep duration in infancy might be predictive of the development of emotional and behavioral problems later in childhood.

Study objectives: Inflammatory and immune mechanisms are considered in restless legs syndrome (RLS) pathophysiology with several autoimmune diseases associated with RLS. There is a paucity of studies examining RLS prevalence in myasthenia gravis (MG), an autoimmune neuromuscular disease. This study investigated RLS prevalence and association with patient-reported measures in a large registry of participants with MG using a validated RLS diagnostic questionnaire.

Methods: The Myasthenia Gravis Foundation of America MG Patient Registry is used on a semiannual basis to survey participants with MG. Patients aged ≥ 18 years, living in the United States, and answering "yes" to physician diagnosed MG were invited by email to enroll in an RLS-customized web-based survey. Collection of data included demographics, disease variables, patient-reported measures with a simple depression scale, MG-quality of life-15 revised, MG-activities of daily living instruments, and 13-item short-form Cambridge-Hopkins diagnostic questionnaire for RLS. Multivariable logistic regression models explored the association between RLS and MG variables of interest.

Results: A total of 630 eligible participants with MG (age: 62.8 ± 13.2; 54.9% female; 91.6% White) completed the survey. The overall prevalence of RLS was 14.8%. The prevalence of clinically significant RLS was 8.4%. The odds of having RLS were increased with higher (worse) MG-activities of daily living, MG-quality of life-15 revised, and depression scores. History of "thymic tumor with thymectomy" and "continuous positive airway pressure therapy" were also independent predictors of RLS.

Conclusions: RLS is common in patients with MG and is associated with worse functional status, quality of life, and depression. The thymus could play a key role in an autoimmune process associating MG with RLS.

Citation: AlGaeed M, McPherson T, Lee I, et al. Prevalence of restless legs and association with patient-reported outcome measures in myasthenia gravis. J Clin Sleep Med. 2025;21(2):269-276.

Study objectives: Obstructive sleep apnea is considered a risk factor for sleepiness at the wheel and near-miss accidents (NMA). To date, there are subjective and objective methods such as the Maintenance of Wakefulness Test (MWT) to investigate sleepiness. However, these methods have limitations. Therefore, a new analysis of the MWT was introduced based on the identification of microsleeps (MS). So, we tested MS analysis to improve the discriminative ability of MWT in recognizing individuals at risk for sleepiness at the wheel and NMA in a population with obstructive sleep apnea.

Methods: The study was conducted on 100 naïve patients with suspected obstructive sleep apnea referred to our Sleep Medicine Unit. All patients performed a full standard polysomnography and MWT. The MWT was analyzed according to standard criteria, and the presence of MS episodes, the mean MS latency, and the MS density (the mean absolute or relative number of MS) were assessed.

Results: MS were observed in 100% of alert or sleepy patients and 47% of the fully alert patients (P < .0001). Almost 90% of patients reporting NMA showed episodes of MS during MWT. The occurrence of NMA was related to excessive daytime sleepiness, MS latency, and MS density (P < .001). The discriminative power for the NMA of MS density measures was higher than that derived from latency analysis, particularly in patients without excessive daytime sleepiness and with a simultaneous mean sleep latency > 33 minutes.

Conclusions: MS analysis provides objective evidence of sleepiness and, therefore, could improve the discriminative ability of the MWT in recognizing individuals at high risk for accidents.

Citation: Tondo P, Pronzato C, Risi I, et al. The role of microsleeps to estimate sleepiness at the wheel and near-miss accidents in obstructive sleep apnea. J Clin Sleep Med. 2025;21(2):287-295.

Study objectives: U-Sleep is a publicly available automated sleep stager, but has not been independently validated using pediatric data. We aimed to (1) test the hypothesis that U-Sleep performance is equivalent to trained humans, using a concordance dataset of 50 pediatric polysomnogram excerpts scored by multiple trained scorers, and (2) identify clinical and demographic characteristics that impact U-Sleep accuracy, using a clinical dataset of 3,114 polysomnograms from a tertiary center.

Methods: Agreement between U-Sleep and "gold" 30-second epoch sleep staging was determined across both datasets. Utilizing the concordance dataset, the hypothesis of equivalence between human scorers and U-Sleep was tested using a Wilcoxon 2 1-sided test. Multivariable regression and generalized additive modeling were used on the clinical dataset to estimate the effects of age, comorbidities, and polysomnographic findings on U-Sleep performance.

Results: The median (interquartile range) Cohen's kappa agreement of U-Sleep and individual trained humans relative to "gold" scoring for 5-stage sleep staging in the concordance dataset were similar, kappa = 0.79 (0.19) vs 0.78 (0.13), respectively, and satisfied statistical equivalence (2 1-sided test P < .01). Median (interquartile range) kappa agreement between U-Sleep 2.0 and clinical sleep-staging was kappa = 0.69 (0.22). Modeling indicated lower performance for children < 2 years, those with medical comorbidities possibly altering sleep electroencephalography (kappa reduction = 0.07-0.15) and those with decreased sleep efficiency or sleep-disordered breathing (kappa reduction = 0.1).

Conclusions: While U-Sleep algorithms showed statistically equivalent performance to trained scorers, accuracy was lower in children < 2 years and those with sleep-disordered breathing or comorbidities affecting electroencephalography. U-Sleep is suitable for pediatric clinical utilization provided automated staging is followed by expert clinician review.

Citation: Kevat A, Steinkey R, Suresh S, et al. Evaluation of automated pediatric sleep stage classification using U-Sleep: a convolutional neural network. J Clin Sleep Med. 2025;21(2):277-285.

Study objectives: Arousal burden (AB) is defined as the cumulative duration of arousals during sleep divided by the total sleep time. However, in-depth analysis of AB related to sleep characteristics is lacking. Based on previous studies addressing the arousal index, we hypothesized that the AB would peak in the supine sleeping position and during non-rapid eye movement stage 1 and show high variability between scorers.

Methods: Nine expert scorers analyzed polysomnography recordings of 50 participants, the majority with an increased risk for obstructive sleep apnea. AB was calculated in different sleeping positions and sleep stages. A generalized estimating equation was used to test the association between AB and sleeping positions, sleep stages, and scorers. The correlation between AB and arousal index was tested with Spearman's rank-order correlation.

Results: AB significantly differed between sleeping positions (P < .001). The median AB in the supine sleeping position was 47-62% higher than in the left and right positions. The AB significantly differed between the sleep stages (P < .001); the median AB was more than 200% higher during non-rapid eye movement stage 1 than during other sleep stages. In addition, the AB differed significantly between scorers (P < .001) and correlated strongly with arousal index (r = .935, P < .001).

Conclusions: AB depends on the sleeping position, sleep stage, and scorer, as hypothesized. AB behaved similarly to the arousal index, but the high variability in the ABs between scorers indicates a potential limitation caused by subjective manual scoring. Thus, the development of more accurate techniques for scoring arousals is required before AB can be reliably used.

Citation: Pitkänen M, Huovinen J, Rissanen M, et al. Arousal burden is highest in supine sleeping position and during light sleep. J Clin Sleep Med. 2025;21(2):337-344.