Reply to Comment on "Associations between sleep quality, excessive daytime sleepiness, and theta wave activity during resting-state electroencephalography in maintenance hemodialysis patients" by Dr. Sanapala K, Mehta R, and Sah R (https://doi.org/10.1007/s11255-025-04659-z)
Hung DV, Toan PQ, Ngoc NT, Thang LV, Thuan DD, Van Quan L, Tai PT, Van Nhat D, Lang HN, Xuan NT and Thao PN
Reply to Comment on "Associations between sleep quality, excessive daytime sleepiness, and theta wave activity during resting-state electroencephalography in maintenance hemodialysis patients" by Dr. Sanapala K, Mehta R, and Sah R (https://doi.org/10.1007/s11255-025-04659-z)
Hung DV, Toan PQ, Ngoc NT, Thang LV, Thuan DD, Van Quan L, Tai PT, Van Nhat D, Lang HN, Xuan NT and Thao PN
Uncovering Sleep Behaviour in Women's Football: What Evidence Do We Have?
Halson SL, Bender A, Howatson G and Pedlar C
Uncovering Sleep Behaviour in Women's Football: What Evidence Do We Have?
Halson SL, Bender A, Howatson G and Pedlar C
Sleep plays an important role in performance, health and well-being, yet may represent a challenge to many female football players. Areas of the brain that are involved in the regulation of sleep contain receptors for the ovarian hormones, estrogen and progesterone. While limited evidence exists describing sleep across the menstrual cycle in elite female football players, related data suggest that female athletes may report poor subjective sleep, despite appropriate objectively measured sleep quality and quantity, particularly prior to or during menstruation. Some of the precipitators of poor sleep in female athletes may include: travel and jetlag, caffeine consumption, light exposure, competing at night, menstrual cycle symptoms, menstrual cycle dysfunction, low iron status and performing caring responsibilities. This article discusses potential approaches to protect, assess and provide interventions to support sleep in female football players. Despite the evidence base of research being predominantly studies of male athletes, there are a number of specific recommendations that can be made for female athletes. These include advice regarding methods to assess sleep and provide interventions based on resource availability, monitoring and managing menstrual cycle symptoms and menstrual dysfunction, and consideration of mitigating strategies to reduce the effects on known sleep disruptors. Many female footballers navigate unique challenges related to sleep; however, with appropriate support from coaches and sport science and sports medicine practitioners, an appropriate support network can be provided to not only optimise performance, but the physical and mental health of female athletes.
Physical and Mental Recovery for Female Footballers: Considerations and Approaches for Better Practice
Howatson G, Russell S, Pedlar C and Halson S
Physical and Mental Recovery for Female Footballers: Considerations and Approaches for Better Practice
Howatson G, Russell S, Pedlar C and Halson S
Increased physiological demands in elite women's football coupled with growing demands on and off the field of play have inevitably placed more pressure on players. Recovery therefore plays a critical role in sustaining health and maintaining high performance for training and readiness to compete. Recovery strategies start with the fundamental need for adequate sleep quality and duration, and nutrition. When these are in place, recovery could be further augmented with additional recovery techniques. Where there is a priority to maximise an adaptative response, there is an argument to withhold additional recovery strategies to maximise the adaptation stimulus. Conversely, when rapid recovery is desired for an imminent match, or in a tournament setting, the application of recovery strategies must be prioritised. This article discusses the approaches that should be considered to support physical and mental recovery and regeneration strategies in the context of women's football. Whilst most recovery research is based on studies of male athletes, there is also work that exclusively focusses on female individuals; this article highlights the potential applicability of this collective work and specific considerations for female football players and offers practical recommendations. Although far from complete, there is emerging evidence of an interplay between cyclical variations of reproductive hormones, associated menstrual cycle/hormonal contraception symptoms and recovery/adaptation. Whilst there is an expected individual variability in menstrual cycle and symptoms, these additional female-specific considerations might contribute to the total stress and recovery needs of the individual athlete. Exploring the role of recovery strategies in support of training and competition for female football players represents an exciting area for future research.
Exploring the Causal Effect of Mitochondrial DNA Copy Number on Obstructive Sleep Apnea
Ji P, Fan Y, Li J, Deng Z, Zhang G and Du J
Exploring the Causal Effect of Mitochondrial DNA Copy Number on Obstructive Sleep Apnea
Ji P, Fan Y, Li J, Deng Z, Zhang G and Du J
Although some studies have established a clear association between mitochondrial DNA (mtDNA) copy number and obstructive sleep apnea (OSA), the causative relationship between the two remains unclear, which is what this study aims to explore.
Hospital-Wide Implementation, Clinical Outcomes, and Safety of Phenobarbital for Alcohol Withdrawal
Wolpaw BJ, Oren H, Quinnan-Hostein L, Bradley KA, Johnson NJ, Hallgren KA, Gupta A, Kim HN, Granich MA and Steel TL
Hospital-Wide Implementation, Clinical Outcomes, and Safety of Phenobarbital for Alcohol Withdrawal
Wolpaw BJ, Oren H, Quinnan-Hostein L, Bradley KA, Johnson NJ, Hallgren KA, Gupta A, Kim HN, Granich MA and Steel TL
Phenobarbital monotherapy is increasingly used to treat alcohol withdrawal syndrome (AWS) in hospitalized patients, but its implementation outside academic emergency departments (EDs) and intensive care units (ICUs) remains understudied.
Non-Direct Contact ECG Signal Classification Using a Hybrid Deep Learning Framework with Validation in Bedside Heart Rate Variability Analysis
Xiao Z, De Vos M, Chatzichristos C, Jiang Y, Zhao M, Ding F, Yang C, Li J and Liu C
Non-Direct Contact ECG Signal Classification Using a Hybrid Deep Learning Framework with Validation in Bedside Heart Rate Variability Analysis
Xiao Z, De Vos M, Chatzichristos C, Jiang Y, Zhao M, Ding F, Yang C, Li J and Liu C
In recent years, the demand for smart healthcare solutions have heightened the need for accuracy, reliability, and comfort in bedside ECG recording and analysis. This study presents a bedside non-direct contact ECG recording system based on capacitive coupling electrocardiography (cECG) and verifies its performance in accurately capturing Heart Rate Variability (HRV) during the night. Firstly, cECG collects ECG data through clothing, avoiding skin irritation from conventional wet electrodes. Secondly, leveraging the unique characteristics of cECG signals, a deep learning framework assesses the quality of cECG, filtering noise and identifying off-bed information, enhancing HRV analysis precision. Subsequently, the system was employed to recording sleep data from 6 subjects overnight, with our proposed algorithm utilized for signal quality assessment (SQA) and HRV analysis. Finally, HRV features were compared with synchronously collected wet electrode ECG signals, encompassing time domain features, frequency domain features, and nonlinear features, totaling 13 HRV features. Experimental findings demonstrate that for the SQA task, the model achieved a classification accuracy of 94.7%, with a Recall of 0.941, Precision of 0.940, F1 score of 0.941, and Cohen's Kappa of 0.927. The accuracy of on/off-bed monitoring reached 99.79%. Additionally, HRV features showed a strong correlation with the reference ECG. In the time-domain metrics, the largest mean absolute percentage error (MAPE) is for PNN50, with a value of 8.148%. In the frequency-domain features, the largest MAPE is for HF, with a value of 13.253%. For nonlinear features, the largest MAPE is for SD1, with a value of 5.182%. Generally, the system exhibited a reliable solution for cECG recording, on/off-bed status detection, and bedside HRV analysis.
Evaluation of Scoring Reliability in Polysomnography at a Single Sleep Center in Thailand
Saiborisut N, Pugongchai A, Tepwimonpetkun C and Ladthavorlaphatt K
Evaluation of Scoring Reliability in Polysomnography at a Single Sleep Center in Thailand
Saiborisut N, Pugongchai A, Tepwimonpetkun C and Ladthavorlaphatt K
The reliability of Thai certificate qualifications for Advanced Sleep Technicians (ASTs) and Sleep Disorders Specialists (SDSs) in manual polysomnography (PSG) scoring has not been previously evaluated. This study assessed the reliability of PSG scoring performed by ASTs, an SDS, and an automated scoring system (AUTO) at Thammasat University Hospital, Thailand. A retrospective analysis of 250 PSG recordings conducted between September 2022 and February 2023 classified patients into four groups based on the apnea-hypopnea index (AHI): No OSA (AHI <5), mild OSA (AHI 5-15), moderate OSA (AHI 15-30), and severe OSA (AHI >30), comprising 11, 77, 105, and 57 cases, respectively. Scoring reliability was compared among ASTs, SDSs, and AUTO. A single-blinded SDS independently scored the PSG data without knowing the AST's scoring to ensure an unbiased assessment. Across more than 630,000 epochs, the Kappa (κ) statistic demonstrated stronger agreement between AST and SDS (κ = 0.980, 95% CI 0.976-0.984) than between AST and AUTO (κ = 0.599, 95% CI 0.543-0.655), indicating significant differences ( < .0001). For mixed apneas (MAs), intraclass correlation coefficients (ICCs) showed the highest consistency between AST and SDS (ICC = 0.998, 95% CI 0.997-0.998) compared to AST and AUTO (ICC = 0.869, 95% CI 0.836-0.897). Significant differences were observed between AST and SDS compared to AST and AUTO across most metrics (P < .0487). While ASTs and SDSs demonstrated excellent scoring consistency, AUTO scoring was notably less accurate, suggesting that the AUTO system requires further refinement to ensure reliable clinical use.
The Where and the Why of Obstructive Sleep Apnea
Tolbert TM
The Where and the Why of Obstructive Sleep Apnea
Tolbert TM
Encouraging General Practitioners to Refer Patients With Insomnia to a Digital Therapeutic (Sleepio): Feasibility Repeated-Measures Intervention Study
Alkhaldi O, McMillan B and Ainsworth J
Encouraging General Practitioners to Refer Patients With Insomnia to a Digital Therapeutic (Sleepio): Feasibility Repeated-Measures Intervention Study
Alkhaldi O, McMillan B and Ainsworth J
Sleepio, a digital therapeutic offering digital cognitive behavioral therapy for insomnia, has been recommended by the National Institute for Health and Care Excellence in the United Kingdom as an alternative to offering sleep hygiene or sleeping pills. However, understanding of the referral behavior of general practitioners (GPs) regarding Sleepio is lacking.
What to Consider When Developing Multidomain Mobile Health Interventions for Lifestyle Management
Weber M, Mattli R, Raab AM, Frei A, Haas K, Marcin T, Vorster A and Schmitt KU
What to Consider When Developing Multidomain Mobile Health Interventions for Lifestyle Management
Weber M, Mattli R, Raab AM, Frei A, Haas K, Marcin T, Vorster A and Schmitt KU
Mobile health (mHealth) interventions can transform health care delivery and improve public health. At the same time, the evidence on lifestyle interventions continues to grow. They show promising results in preventing and treating noncommunicable diseases and enhancing health-related quality of life. These factors highlight the potential of multidomain mHealth interventions for lifestyle management. This viewpoint paper focuses on drawing valuable lessons from past experiences and providing guidance to developers of mHealth interventions for lifestyle management. We underscore the critical role of sharing practical insights to advance innovation in the field of mHealth interventions. We used an iterative consensus process to derive lessons learned, identify challenges, and reflect on possible actions. Our insights are based on our experience in developing 2 smartphone-based lifestyle interventions. Challenges and corresponding options in the following areas are presented: target population (preferences, personalization, and delivery), user involvement and testing, human support, and multidomain interventions (interdisciplinarity, flexibility, and core team). The development of multidomain mHealth interventions for lifestyle management requires a participatory and iterative approach involving relevant stakeholders (including end users) so that the right people get the right content at the right time. Additionally, it is crucial to consider established frameworks, guidelines, and regulations; allocate appropriate resources; and form a core team committed to the project's aims and open to working in an interdisciplinary team.
