Background. Many women with perimenopausal insomnia (PMI) have sought alternative therapies such as acupuncture because of concerns about risks associated with hormone replacement therapy (HRT) and/or psychotropic drugs. This systematic review aimed to clarify if acupuncture alone or combined with standard Western pharmacotherapy (HRT and/or psychotropic drugs) is more effective in ameliorating PMI in comparison to pharmacotherapy alone. Methods. Randomized controlled trials (RCTs) of PMI treatment via acupuncture alone or combined with Western pharmacotherapy versus Western pharmacotherapy were searched for from eleven databases from inception to March 2020. Cochrane criteria were followed. Results. Fifteen studies involving 1410 women were analyzed. Meta-analysis indicated that acupuncture significantly reduced the global scores of Pittsburgh Sleep Quality Index (PSQI) [MD = −2.38, 95% CI (−3.38, −1.37), < 0.01] and Kupperman Index [MD = −5.95, 95% CI (−10.68, −1.21), = 0.01], compared with hypnotics. Acupuncture combined with hypnotics was more effective than hypnotics alone in decreasing PSQI scores [MD = −3.13, 95% CI (−5.43, −0.83), < 0.01]. Too few RCTs were available to investigate the clinical efficacy differences between acupuncture and HRT/psychotropic drugs other than hypnotics. Conclusions. Despite limited evidence, in comparison to hypnotics, acupuncture was associated with significant improvements in PMI, and reductions of other menopausal symptoms. This finding suggests that acupuncture may be a useful addition to treatment for PMI.

Background: Acupuncture, as an important component of traditional Chinese medicine (TCM), has been widely applied in the treatment of chronic insomnia in China, while there is no clinical study related to its therapeutic mechanism. Methods/design: A single-center, single-blind, randomized, placebo-controlled trial will be conducted at Jiangsu Hospital of Traditional Chinese Medicine. A total of 60 patients will be registered. Eligible participants will be randomly divided into acupuncture group and sham acupuncture group (n = 30 cases in each group). Patients in both groups will be treated once every other day, three times per week for 4 weeks. The primary outcome measures are Pittsburgh Sleep Quality Index (PSQI) and concentrations of adrenocorticotropic hormone (ATCH), corticotrophin-releasing hormone (CRH), and cortisol (CORT). Secondary outcome measures are Insomnia Severity Index (ISI) and Fatigue Severity Scale (FSS). Discussion: This study aims to evaluate the therapeutic effects of acupuncture on chronic insomnia by using PSQI, ISI, and FSS. The mechanism of acupuncture on CIPs will be preliminarily discussed by analyzing the changes in concentrations of CRH, ACTH, and CORT before and after treatment. Trial registration: Chinese Clinical Trials Register, ChiCTR1800020298.

Background: The benefits of acupuncture on primary insomnia (PI) have been well established in previous studies. However, different acupuncture dosages may lead to controversy over its efficacy. Therefore, this systematic review and meta-analysis was conducted to assess the relationship between the dose and efficacy of acupuncture for the treatment of PI.Methods: Seven databases were searched from inception until May 30, 2024. The included randomized controlled trials (RCTs) with acupuncture for PI on the Pittsburgh Sleep Quality Index (PSQI) scores were divided into three categories according to the therapeutic dose of acupuncture (frequency, session, and course): low dosage, medium dosage, and high dosage. The correlation between the dose and the effect of treatment was analyzed. Risk of bias was assessed using Cochrane Collaboration’s risk of bias tool. Meta-analyses were performed using RevMan v.5.4 and Stata 16.0 software.Results: A total of 56 studies were included. There were 17 sham acupuncture-controlled RCTs that are notable because of their high quality. Overall, the effect on the reduction of the PSQI scores varied across the different acupuncture dosages. For the frequency of acupuncture, the results showed a significant improvement in the moderate frequency (three sessions per week) and high frequency (five to seven sessions per week) categories. With regard to the acupuncture session, it was shown that moderate session (12–20 sessions) and high session (24–30 sessions) had better effects on the reduction of the PSQI scores, with low session (≤10 sessions) being not significant. For the acupuncture course, there were no differences in the short course (≤2 weeks) and the long course (>4 weeks) between the acupuncture group and the control group. Medium course (3–4 weeks) was considered as the optimal course. In addition, there were no differences between acupuncture and SATV (sham acupuncture therapy at verum points) on the same acupuncture points in the PSQI scores. The results of GRADE assessment demonstrated that the level of evidence was very low to moderate, probably due to the poor methodological quality and the substantial heterogeneity among studies.Conclusions: A dose–effect relationship was found between the acupuncture dose and the PSQI scores. Although sham acupuncture needling at the same points as those in acupuncture may not be a true placebo control, this was utilized in a minority of studies. Collectively, the data suggest that at least three sessions per week for 3–4 weeks and a total of at least 12 acupuncture sessions would be the optimal clinical response.Systematic review registration: https://www.crd.york.ac.uk/, identifier CRD42024560078.

Objective: The number of citations to a paper represents the weight of that work in a particular area of interest. Several highly cited papers are listed in the bibliometric analysis. This study aimed to identify and analyze the 100 most cited papers in insomnia research that might appeal to researchers and clinicians.Methods: We reviewed the Web of Science (WOS) Core Collection database to identify articles from 1985 to 24 March 2022. The R bibliometric package was used to further analyze citation counts, authors, year of publication, source journal, geographical origin, subject, article type, and level of evidence. Word co-occurrence in 100 articles was visualized using VOS viewer software.Results: A total of 44,654 manuscripts were searched on the Web of Science. Between 2001 and 2021, the top 100 influential manuscripts were published, with a total citation frequency of 38,463. The top countries and institutions contributing to the field were the U.S. and Duke University. Morin C.M. was the most productive author, ranking first in citations. Sleep had the highest number of manuscripts published in the top 100 (n = 31), followed by Sleep Medicine Reviews (n = 9). The most cited manuscript (Bastien et al., Sleep Medicine, 2001; 3,384 citations) reported clinical validation of the Insomnia Severity Index (ISI) as a brief screening indicator for insomnia and as an outcome indicator for treatment studies. Co-occurrence analyses suggest that psychiatric disorders combined with insomnia and cognitive behavioral therapy remain future research trends.Conclusion: This study provides a detailed list of the most cited articles on insomnia. The analysis provides researchers and clinicians with a detailed overview of the most cited papers on insomnia over the past two decades. Notably, COVID-19, anxiety, depression, CBT, and sleep microstructure are potential areas of focus for future research.

Sleep staging is essential for evaluating sleep quality, diagnosing disorders, and creating personalized treatment plans. The convolutional and bidirectional long short-term memory hybrid neural network (CNN-BiLSTM) has shown promise in automated sleep staging from electroencephalogram (EEG) signals. However, prior studies often overlook expert-derived manual features, relying solely on deep neural networks for automatic feature extraction. This study proposes an automated sleep staging model (named MA-CNN-BiLSTM) for single-channel EEG using a CNN-BiLSTM network with embedded manual features and attention mechanisms. The model computes multidimensional features such as signal energy and entropy via wavelet decomposition and integrates attention mechanisms to enable the network to focus on crucial features for classification. Sleep stage classification is achieved using a SoftMax layer. The proposed MA-CNN-BiLSTM model is validated on the Sleep-EDF-20 and SVUH-UCD datasets, demonstrating superior classification accuracy, macro-averaged F1 scores, and Cohen’s Kappa, outperforming other models.

Objective. To evaluate the clinical efficacy of nonpharmacological interventions in improving balance function of patients with osteoporosis or osteopenia using network meta-analysis (NMA). Methods. We searched seven databases (PubMed, the Cochrane Library, Embase, CKNI, Wanfang Data, VIP, and CBM) for relevant randomized controlled trials (RCTs) up to August 31, 2020. Berg Balance Scale (BBS) and Time Up and Go Test (TUGT) were used as outcome measures. Two researchers independently screened studies, collected data from the studies, and estimated risk of study bias. Divergence in the evaluation process was settled by consulting a third researcher. We used Stata 15.1 software for network meta-analysis (NMA). Results. We identified 10 eligible RCTs, with a total of 737 patients and four intervention methods, including traditional Chinese medicine (TCM) exercises, pulsed electromagnetic fields (PEMFs), strength training, and balance and strength training. The results revealed that all nonpharmacological interventions could improve balance function, but the effect of balance and strength training was better than other interventions. Conclusion. Exercise can significantly improve the balance function of patients with osteoporosis and osteopenia, and balance combined with strength training has the best effect, followed by TCM exercises.