Sleep medicine最新文献

Mean disease alleviation measures the effectiveness of Obstructive Sleep Apnea (OSA) treatments. It combines a patient's adherence to treatment normalized to their total sleep time and the treatment's efficacy as determined by the change in the apnea-hypopnea index. This metric fails to capture the patient's OSA-related symptoms, which are a key component and, in some cases, the primary component, of determining response to treatment. We propose an enhanced metric called three-dimensional mean disease alleviation (3D-MDA), which incorporates the symptom response to better reflect the true treatment impact. RESULTS: The proposed 3D-MDA metric aims to provide a more comprehensive assessment of OSA treatment effectiveness by integrating the subjective impact, therapy adherence, and objective efficacy. Further, 3D-MDA is adaptable over time as the optimal metrics for these categories continue to evolve.

Background: Performing simulated snoring (SS) is a commonly used method to evaluate the source of snoring in obstructive sleep apnea (OSA). SS sounds is considered as a potential biomarker for OSA. SS sounds can be easily recorded, which is a cost-effective method for prescreening purposes.

Objective: This study aimed to validate the performance of artificial intelligence (AI) models using SS sounds for OSA diagnosis.

Methods: All participants underwent full-night polysomnography (PSG) monitoring at the sleep center. SS sounds of the participants were recorded during the laryngoscopy procedure. The audio data were processed via Python, and relevant features were extracted. OSA diagnostic models were developed using three machine learning (ML) algorithms and one deep learning (DL) algorithm. The diagnostic performance was evaluated by multiple indicators.

Results: A total of 465 participants were included. For the support vector machine algorithm, the accuracy values at apnea-hypopnea index (AHI) levels of 5, 15, and 30 per hour were 0.914, 0.887, and 0.807, respectively. For the K-nearest neighbor algorithm, the accuracy values at AHI levels of 5, 15, and 30 per hour were 0.896, 0.872, and 0.756, respectively. For the random forest algorithm, the accuracy values at AHI levels of 5, 15, and 30 per hour were 0.905, 0.881, and 0.804, respectively. For the audio spectrogram transformer algorithm, the accuracy values at AHI levels of 5, 15, and 30 per hour were 0.926, 0.887, and 0.830, respectively.

Conclusions: Our study demonstrates that DL models can effectively screen and identify OSA with commendable performance. In addition, the identification ability of the DL models was better than that of any of the ML models.

Objectives: The diagnosis of Parkinson's disease (PD) is mainly based on the assessment of motor symptoms, although the influence of non-motor symptoms sometimes may be more significant on the patient's disability than the cardinal clinical signs of the disease. The predominant subtype of postural instability and gait disturbance is known to be associated with more severe non-motor symptoms of Parkinson's disease. Yet, the association between motor subtypes and specific mood symptoms remains understudied. The study aimed to analyze an association between sleep and chronotype signs, motor subtypes, with the severity of depressive symptoms in PD patients.

Methods: We have included 64 patients in the clinical study. The studied population was divided into the following groups: PIGD group - patients with PD and dominance of postural instability and gait disorders; non-PIGD group - patients with PD and dominance of tremor or intermediate motor subtype. We used the Unified Parkinson's Disease Rating Scale, Beck Depression Inventory, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Munich Chronotype Questionnaire.

Results: Patients with the PIGD subtype have higher levels of depressive symptoms and excessive daytime sleepiness, poorer sleep quality, later sleep onset and mid-sleep, longer sleep latency, and sleep inertia. PIGD motor subtype (p < 0.001), poor sleep quality (p < 0.001), mid-sleep (p = 0.016), and sleep latency (p = 0.025) had a significant impact on the level of depression in univariate regression analysis. Still, only mid-sleep (p = 0.019) and poor sleep quality (p = 0.003) increased the probability of higher severity of depression in the multivariate model.

Conclusion: Poor sleep quality and later mid-sleep may be predictors of more severe depressive symptoms in PD.

Objective: The decline in sleep quality induced by hypoxia is the main environmental exposure risk affecting the physiological health of high-altitude residents. The long-term effects of oxygen therapy on the sleep quality and health of highlanders remain unclear. This study aims to evaluate the impact of chronic oxygen therapy on sleep and health, providing a scientific basis for the establishment of regional centralized oxygen supply and the implementation of health regulations to improve sleep quality and health in plateau areas.

Methods: Conducted over a span of three years at an altitude of 3255 m in the Tibetan Plateau, this study included 317 participants and meticulously recorded sleep data for 1398 nights. The generalized estimation equation was used to analyze the impact of oxygen supply on sleep quality, physiological parameters, and indoor environment.

Results: The research found that long-term oxygen therapy significantly reduced the pulse rate of highland residents, increased their blood oxygen saturation, and consequently decreased their risk of cardiovascular disease. Oxygen-enriched environments improved the sleep quality of highland dwellers, significantly increasing their sleep efficiency, duration of rapid eye movement sleep and deep sleep, and subjective sleep quality evaluation, while also significantly reducing central sleep apnea-induced nighttime awakening events.

Conclusions: Long-term chronic oxygen therapy is beneficial to highland residents in terms of sleep respiratory rhythm, sleep quality, and cardiovascular function. It is imperative for both the local inhabitants of high-altitude areas and the local health authorities to be aware of the risks of hypoxia and the health benefits of oxygen therapy.

Background: Restless Legs Syndrome (RLS) is a common neurological disorder currently diagnosed based on clinical features only, and characterized by a compulsive urge to move the legs triggered by rest or diminished arousal. This systematic review aimed at integrating all current brain magnetic resonance imaging (MRI) modalities for a convergent pathophysiological understanding of RLS phenomenology.

Methods: We performed a MEDLINE (PubMed)-based systematic review for research articles in patients with primary RLS published in English from 2010 till November 2023. Studies meeting the inclusion criteria according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria were systematically assessed for quality using modality-specific checklists, bias using AXIS tool and a narrative synthesis of the results was conducted.

Results: A total of 49 studies (22 structural, 12 DTI, 7 iron-imaging, 4 spectroscopy with 10 datasets combining multiple approaches) involving 1273 patients (414 males) and 1333 healthy controls (478 males) met the eligibility criteria. Despite participant, technical/device-related and statistical heterogeneity, most agree that patients with primary RLS have structural and metabolite alterations, changes in multiple white matter tract architectures, and disrupted functional connectivity within multiple brain areas. Most of the studies (n = 43, 88 %) have a low-risk of bias on the AXIS scale. Scores on the modality-specific checklist ranged from 46 to 92 %, 70-93 % and 54-92 % for structural MRI, DTI and MRS Datasets, respectively.

Conclusions: Notwithstanding the large heterogeneity in the methods employed, global connectivity alterations suggest the utility of casting RLS within a system-level perspective rather than viewing it as related to the dysfunction of a single or particular brain region. A holistic approach and its integration within the framework of molecular vulnerability and neurotransmitter alterations are warranted to disentangle the complex pathophysiology of RLS and to identify new therapeutic targets.

We analyze data of the prevalence of sleep disturbance among Chinese healthcare professionals and maintain that they increase Eastward, refining previous results. We suggest that position in time zone is a valid explanatory metric only after daily rhythms have been uniformed. On a more general note, this finding suggest that daylight saving time might help reduce sleep disturbance.