{"title":"Using Bioinformatics and Machine Learning to Predict the Genetic Characteristics of Ferroptosis-Cuproptosis-Related Genes Associated with Sleep Deprivation.","authors":"Liang Wang, Shuo Wang, Chujiao Tian, Tao Zou, Yunshan Zhao, Shaodan Li, Minghui Yang, Ningli Chai","doi":"10.2147/NSS.S473022","DOIUrl":"https://doi.org/10.2147/NSS.S473022","url":null,"abstract":"<p><strong>Purpose: </strong>Sleep deprivation (SD), a common sleep disease in clinic, has certain risks, and its pathogenesis is still unclear. This study aimed to identify ferroptosis-cuproptosis-related genes (FCRGs) associated with SD through bioinformatics and machine learning, thus elucidating their biological significance and clinical value.</p><p><strong>Methods: </strong>SD-DEGs were obtained from GEO. We intersected key WGCNA module genes of DE-FCRGs with SD-DEGs to obtain SD-DE-FCRGs. GO and KEGG analyses were performed. Machine learning was used to screen SD-DE-FCRGs, and filtered genes were intersected to obtain SD characteristic genes. ROC curves were used to evaluate the accuracy of SD characteristic genes. CIBERSORT was used to analyze the correlation between SD-DE-FCRGs and immune cells. We constructed a ceRNA network of SD-DE-FCRGs and used DGIbd to predict gene drug targets.</p><p><strong>Results: </strong>The 156 DEGs were identified from GSE98566. Five SD-DE-FCRGs from DE- FCRGs and SD-DEGs were analyzed via WGCNA, and enrichment analysis involved mainly ribosome regulation, mitochondrial pathways, and neurodegenerative diseases. Machine learning was used to obtain Four SD-DE-FCRGs (IKZF1, JCHAIN, MGST3, and UQCR11), and these gene analyses accurately evaluated the distribution model (AUC=0.793). Immune infiltration revealed that SD hub genes were correlated with most immune cells. Unsupervised cluster analysis revealed significant differential expression of immune-related genes between two subtypes. GSVA and GSEA revealed that enriched biological functions included oxidative phosphorylation, ribonucleic acid, metabolic diseases, activation of oxidative phosphorylation, and other pathways. Four SD-DE-FCRGs associated with 29 miRNAs were identified via the construction of a ceRNA network. The important target lenalidomide of IKZF1 was predicted.</p><p><strong>Conclusion: </strong>We first used bioinformatics and machine learning to screen four SD-DE-FCRGs. These genes may affect the involvement of infiltrating immune cells in pathogenesis of SD by regulating FCRGs. We predicted that lenalidomide may target IKZF1 from SD-DE-FCRGs.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 ","pages":"1497-1513"},"PeriodicalIF":3.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Phase-Amplitude Coupling in Theta and Beta Bands: A Potential Electrophysiological Marker for Obstructive Sleep Apnea.","authors":"Chan Zhang, Yanhui Wang, Mengjie Li, Pengpeng Niu, Shuo Li, Zhuopeng Hu, Changhe Shi, Yusheng Li","doi":"10.2147/NSS.S470617","DOIUrl":"https://doi.org/10.2147/NSS.S470617","url":null,"abstract":"<p><strong>Background: </strong>Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function.</p><p><strong>Methods: </strong>: We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices.</p><p><strong>Results: </strong>Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%).</p><p><strong>Conclusion: </strong>OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 ","pages":"1469-1482"},"PeriodicalIF":3.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423842/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predicting Depression Among Chinese Patients with Narcolepsy Type 1: A Machine-Learning Approach","authors":"Mengmeng Wang, Huanhuan Wang, Zhaoyan Feng, Shuai Wu, Bei Li, Fang Han, Fulong Xiao","doi":"10.2147/nss.s468748","DOIUrl":"https://doi.org/10.2147/nss.s468748","url":null,"abstract":"<strong>Objective:</strong> Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches.<br/><strong>Methods:</strong> A total of 203 drug-free NT1 patients (aged 5– 61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People’s Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA).<br/><strong>Results:</strong> The LR model identified hallucinations (OR 2.21, 95% CI 1.01– 4.90, <em>p</em> = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02– 1.18, <em>p</em> = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors.<br/><strong>Conclusion:</strong> This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.<br/><br/><strong>Keywords:</strong> narcolepsy type 1, depression, machine learning, support vector machine<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"187 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Guo, Ying Xu, Yao Meng, Hao Lian, Jingwen He, Ruike Zhang, Jingzhou Xu, Hao Wang, Shuyu Xu, Wenpeng Cai, Lei Xiao, Tong Su, Yunxiang Tang
{"title":"Acute Aerobic Exercise Intensity on Working Memory and Vigilance After Nap Deprivation: Effects of Low-Intensity Deserve Attention","authors":"Xin Guo, Ying Xu, Yao Meng, Hao Lian, Jingwen He, Ruike Zhang, Jingzhou Xu, Hao Wang, Shuyu Xu, Wenpeng Cai, Lei Xiao, Tong Su, Yunxiang Tang","doi":"10.2147/nss.s471930","DOIUrl":"https://doi.org/10.2147/nss.s471930","url":null,"abstract":"<strong>Background:</strong> Napping deprivation in habitual nappers leads to cognitive impairment. The ameliorative effect of acute aerobic exercise has been demonstrated for this post-cognitive impairment. However, it is still unclear which intensity of aerobic exercise is the most effective and how long this improvement can be sustained.<br/><strong>Methods:</strong> Fifty-eight healthy adults with a chronic napping habit were randomly assigned to four intervention groups after undergoing nap deprivation: a sedentary control group, a low-intensity exercise group (50– 59% maximum heart rate, HR<sub>max</sub>), a moderate-intensity exercise group (60– 69% HR<sub>max</sub>), and a high-intensity exercise group (70– 79% HR<sub>max</sub>). Working memory (N-back task), vigilance (Psychomotor Vigilance Task, PVT), and response inhibitory capacity (Go/NoGo task) were measured.<br/><strong>Results:</strong> Regression analyses showed a quadratic trend between exercise intensity and working memory reaction time and accuracy (<em>F</em> =3.297– 5.769, <em>p</em> < 0.05, <em>R<sup>2</sup></em> =10.7– 18.9%). The effects of exercise were optimal at low-intensity. There was a significant quadratic trend between exercise intensity and PVT lapse (<em>F</em> =4.314, <em>p</em> =0.042, <em>R²</em> =7.2%). The effect of exercise increased with higher intensity. Prolonged observation found that the effect of low-intensity exercise on working memory was maintained for 2 hours.<br/><strong>Conclusion:</strong> The effect of low-intensity exercise might be underestimated. Low-intensity exercise significantly improved working memory performance, and the effects could be maintained throughout the afternoon. In contrast, the effects of high-intensity exercise were unlikely to be maintained and might even have negative effects. Future researchers can broaden the categories of participants to enhance the external validity and collect diverse physiological indicators to explore related physiological mechanisms.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"75 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Abnormal N-Acetylaspartate to Creatine Ratio of the Right Putamen is Linked to Wakefulness in Patients with Insomnia Disorder","authors":"Qiaoting Huang, Changzheng Shi, Saurabh Sonkusare, Congrui Li, Valerie Voon, Jiyang Pan","doi":"10.2147/nss.s468269","DOIUrl":"https://doi.org/10.2147/nss.s468269","url":null,"abstract":"<strong>Purpose:</strong> Converging evidence implicates the putamen in sleep-wake regulation. However, its role remains unclear. We hypothesized that metabolic abnormalities in the putamen are linked to insomnia disorder, which has not been previously addressed, and investigated putaminal N-acetylaspartate (NAA), choline (Cho), and creatine (Cr) in patients with insomnia disorder compared to healthy controls.<br/><strong>Participants and Methods:</strong> In the present study, the concentrations of NAA, Cho, and Cr in the putamen of 23 patients with insomnia disorder and 18 healthy controls were determined using proton magnetic resonance spectroscopy. Sociodemographic, psychometric, and polysomnography data were obtained from all participants.<br/><strong>Results:</strong> We found that the mean NAA/Cr ratio of the right putamen was significantly greater in the insomnia group compared to the control group and also greater than the left putamen within the insomnia group. The NAA/Cr ratio of the right putamen distinguished insomnia disorder from normal sleep with 78.3% sensitivity and 61.1% specificity. Furthermore, this ratio positively correlated with both objective and subjective insomnia severity and sleep quality.<br/><strong>Conclusion:</strong> Our findings provide critical evidence for the dysfunctional putaminal metabolism of NAA/Cr in insomnia disorder, suggesting that the abnormal NAA/Cr ratio of the right putamen is linked to wakefulness in patients with insomnia disorder and may serve as a potential biomarker of insomnia disorder.<br/><br/><strong>Keywords:</strong> insomnia disorder, wakefulness, putamen, proton magnetic resonance spectroscopy, NAA/Cr ratio, polysomnography<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"31 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ting Yang, Han-Rui Wang, Ya-Kui Mou, Wan-Chen Liu, Yao Wang, Xiao-Yu Song, Chao Ren, Xi-Cheng Song
{"title":"Mutual Influence Between Allergic Rhinitis and Sleep: Factors, Mechanisms, and interventions—A Narrative Review","authors":"Ting Yang, Han-Rui Wang, Ya-Kui Mou, Wan-Chen Liu, Yao Wang, Xiao-Yu Song, Chao Ren, Xi-Cheng Song","doi":"10.2147/nss.s482258","DOIUrl":"https://doi.org/10.2147/nss.s482258","url":null,"abstract":"<strong>Abstract:</strong> Patients with allergic rhinitis (AR) have a high incidence of sleep disorders, such as insomnia, which can easily exacerbate nasal symptoms. The aggravation of nasal symptoms further promotes the deterioration of sleep disorders, forming a vicious cycle. Severe cases may even trigger psychological and neurological issues, such as anxiety, depression, and cognitive impairment, causing significant distress to patients, making clinical diagnosis and treatment difficult, and increasing costs. Furthermore, satisfactory therapeutics remain lacking. As the pathogenesis of AR-associated sleep disorders is not clear and research is still insufficient, paying attention to and understanding AR-related sleep disorders is crucial in clinical practice. Multiple studies have shown that the most crucial issues in current research on AR and sleep are analyzing the relationship between AR and sleep disorders, searching for the influencing factors, and investigating potential targets for diagnosis and treatment. This review aimed to identify and summarize the results of relevant studies using “AR” and “sleep disorders” as search terms. In addition, we evaluated the correlation between AR and sleep disorders and examined their interaction and potential mechanisms, offering a foundation for additional screening of potential diagnostic biomarkers and therapeutic targets.<br/><br/><strong>Keywords:</strong> allergic rhinitis, biological rhythm, immune inflammatory, neurological regulation, sleep disorders<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"16 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of Insufficient Sleep on Myopia in Children: A Systematic Review and Meta-Analysis","authors":"Xixuan Zhao, Yining He, Juzhao Zhang, Senlin Lin, Haidong Zou, Yingyan Ma","doi":"10.2147/nss.s472748","DOIUrl":"https://doi.org/10.2147/nss.s472748","url":null,"abstract":"<strong>Abstract:</strong> Myopia is increasingly prevalent in children. Its association with insufficient sleep has been studied, yielding inconsistent findings. This review aims to assess the association of insufficient sleep with myopia and myopia-related refractive parameters in children. A total of 657 articles were identified, of which 40 were included in the systematic review and 33 were included in the meta-analysis. Results showed that insufficient sleep was significantly associated with an increased prevalence of myopia (odds ratio [OR] = 1.59; 95% confidence interval [CI] = 1.31, 1.95; <em>I</em><sup>2</sup> = 99%), and an increased prevalence of high myopia (OR = 3.36; 95% CI = 1.26, 9.00; <em>I</em><sup>2</sup> = 96%). Shorter sleep duration was significantly linked to faster changes in axial length (AL) (β = 0.05; 95% CI = 0.02, 0.08; <em>I</em><sup>2</sup> = 0%). However, correlation between insufficient sleep and the incidence of myopia, spherical equivalent refraction, corneal curvature radius (CR) and AL/CR were insignificant. Moreover, the effect of insufficient sleep on premyopia and astigmatism was not well-studied. The results of this study suggest that insufficient sleep may be an important risk factor for the development of myopia in school-aged children. Therefore, in addition to ensuring sufficient outdoor activities and reducing near work, it is necessary to inform children and parents about the importance of adequate sleep to mitigate the risk of myopia.<br/><br/><strong>Keywords:</strong> insufficient sleep, myopia, children, axial length, refractive parameters<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"6 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Validation of the Athens Insomnia Scale Among Young Chinese Male Population in a High-Altitude Situation","authors":"Xugang Tang, Qiang Wang, Shuang Li, Xiuchuan Li, Qian Xin, Yongjian Yang","doi":"10.2147/nss.s475497","DOIUrl":"https://doi.org/10.2147/nss.s475497","url":null,"abstract":"<strong>Purpose:</strong> The Athens Insomnia Scale (AIS) is a widely used and authorized questionnaire for evaluating insomnia symptoms. However, its reliability and validity at high altitudes are uncertain. Therefore, this study aimed to confirm the validity and reliability of AIS during a 3658 m altitude exposure.<br/><strong>Patients and Methods:</strong> A total of 387 young Chinese males were enlisted in the acute high-altitude exposure group. They flew for about two hours, climbing from 400 m to 3658 m. The high-altitude-acclimated group consisted of 86 young Chinese men who had lived at least six months at 3658 m altitude. The sleep quality of the acute high-altitude exposure group was evaluated using the AIS before the ascent and after exposure to 3658 m for 24 hours, and one week. The sleep quality of the high-altitude-acclimated group was also assessed. The AIS’s internal consistency, reliability, and validity were evaluated.<br/><strong>Results:</strong> The respondents’ quality of sleep significantly decreased after being exposed to 3658 m as opposed to 400 m. Two factors comprised the AIS, according to an exploratory factor analysis: “sleep problem” (items 1– 5) and “daytime dysfunction” (items 6– 8). The Cronbach’s α internal consistency coefficients exceeded 0.8, and the corrected item-total correlations were all greater than 0.5 when the subjects were exposed to 3658 m. The model fit index was well within the criterion. The average variance extracted and composite reliability were all higher than 0.5 and 0.7, respectively. The interclass correlation coefficient was deemed “fair to good” at 0.482, which is greater than the 0.4 threshold. The AIS has satisfactory discriminant validity, as shown by the Fornell-Larcker criterion and cross-loading results. The daytime dysfunction R-square values (> 0.33) show that the frameworks have considerable predictive accuracy.<br/><strong>Conclusion:</strong> The AIS exhibits strong consistency, reliability, and validity. The AIS’s features and simplicity make it an essential psychometric tool for high-altitude sleep research.<br/><br/><strong>Keywords:</strong> athens insomnia scale, high altitude, internal consistency, reliability, sleep, validity<br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"10 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jia Wei, Mingfen Song, Hong Jing Mao, Ruobing Qi, Lili Yang, You Xu, Pan Yan, Linlin Hu
{"title":"Analysis of the Improvement Sequence in Insomnia Symptoms and Factors Influencing the Treatment Outcomes of Smartphone-Delivered CBT in Patients with Insomnia Disorder","authors":"Jia Wei, Mingfen Song, Hong Jing Mao, Ruobing Qi, Lili Yang, You Xu, Pan Yan, Linlin Hu","doi":"10.2147/nss.s486288","DOIUrl":"https://doi.org/10.2147/nss.s486288","url":null,"abstract":"<strong>Background:</strong> The effectiveness of medication combined with smartphone-delivered cognitive behavioral therapy for insomnia (CBT-I) has been well verified, but there are few studies on the sequence of remission of insomnia symptoms. This study aims to understand the sequence of symptom improvement and the factors influencing the treatment effectiveness in patients with insomnia.<br/><strong>Methods:</strong> Smartphone-delivered CBT, as a form of Online CBT, allows for training through mobile devices at any time and place. We utilized the Good Sleep 365 app to conduct a survey, involving 2820 patients who met the baseline inclusion criteria. These patients were assessed using a general demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI) to evaluate general demographic information and insomnia symptoms, and subsequently underwent CBT training using the Good Sleep 365 app. A total of 1179 patients completed follow-ups at 4 weeks, 8 weeks, 16 weeks, and 24 weeks.<br/><strong>Results:</strong> At 4 weeks and 8 weeks, the descending order of the reduction rates of PSQI components (excluding component 6: use of sleeping medication) was: sleep latency, subjective sleep quality, sleep efficiency, sleep disturbance, sleep maintenance, and daytime dysfunction. At 16 weeks and 24 weeks, the descending order was subjective sleep quality, sleep latency, sleep efficiency, daytime dysfunction, sleep maintenance, and sleep disturbance. There were significant differences in the reduction rates of PSQI components (excluding component 6: use of sleeping medication) both at the same follow-up times and at different follow-up times (all P< 0.05). Multivariable logistic regression analysis showed that patients older than 30 years and those with a college degree or above had better treatment outcomes, whereas those with a disease duration of more than three years had worse outcomes.<br/><strong>Conclusion:</strong> The sequence of symptom improvement in patients with insomnia changes over time, and age, educational level, and duration of disease are factors influencing treatment outcomes.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"4 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Association Between Sleep Characteristics and Likelihood of Prodromal Parkinson’s Disease: A Cross-Sectional Analysis in the HABIT Study","authors":"Cheng-Jie Mao, Hao Peng, Sheng Zhuang, Ying-Chun Zhang, Wei-Ye Xie, Jia-Hui Yan, Hui-Hui Liu, Jing Chen, Jun-Yi Liu, Jianan Zhang, Hai Jiang, Yonghong Zhang, Mingzhi Zhang, Chun-Feng Liu","doi":"10.2147/nss.s476348","DOIUrl":"https://doi.org/10.2147/nss.s476348","url":null,"abstract":"<strong>Background:</strong> Sleep is critical in health problems including Parkinson’s disease (PD). This study examined the association between sleep characteristics and the likelihood of prodromal PD.<br/><strong>Methods:</strong> At baseline examination of the Heart and Brain Investigation in Taicang (HABIT) study, potential PD biomarkers were obtained for 8777 participants aged over 50 years, and the probability of prodromal PD was assessed based on the Chinese expert consensus and Movement Disorder Society (MDS) criteria. General and component sleep characteristics were evaluated by the Pittsburgh Sleep Quality Index (PSQI). Median regression was applied to examine the association between sleep and the probability of prodromal PD, adjusting for age, sex, education level, physical activity, obesity, fast plasma glucose, lipids, and hypertension.<br/><strong>Results:</strong> Based on China criteria, a higher level of PSQI score was significantly associated with a higher probability of prodromal PD (β = 0.02, 95% CI: 0.01– 0.03) and a higher risk of having an increased probability of prodromal PD (OR = 1.04, 95% CI: 1.02– 1.05). Compared to participants with good quality sleep, those with poor quality sleep had a 0.07% increased probability of prodromal PD (95% CI: 0.01– 0.13) and a 19% increased risk of having a high prodromal PD probability (95% CI: 1.04– 1.20). Similar associations between sleep quality and the probability of prodromal PD were also observed using the MDS criteria. Subjective sleep quality, sleep latency, habitual sleep efficiency, daytime dysfunction, and use of sleep medications were also associated with the probability of prodromal PD.<br/><strong>Conclusion:</strong> Poor sleep quality was associated with a high probability of prodromal PD. Sleep may be helpful for understanding and intervention of prodromal PD.<br/><br/>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142201804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}