Sleep-related hypermotor epilepsy （SHE） is a rare type of epilepsy with a prevalence rate of approximately 1.8/100 000. This disease mainly manifests as complex motor behaviors during non-rapid eye movement sleep， such as leg kicking， arm waving， and sitting up. Since such symptoms are similar to non-epileptic disorders such as night terrors and sleepwalking and abnormal discharges may not be observed on electroencephalography， the diagnosis of SHE is quite challenging. Currently， there is still a lack of evidence from large-scale randomized controlled studies to support pharmacological treatment strategies for SHE， and related data in China remain scarce. This article reports a case of SHE， in order to provide a clinical reference for the diagnosis and medication treatment of this disease.
Polysomnography

Objective To investigate the sleep architecture of sleep related bruxism（SB）in adults and the sleep architecture of SB comorbid with obstructive sleep apnea hypopnea syndrome（OSAHS），as well as their correlation with age and other factors. Methods A total of 51 subjects with SB and 67 controls were included in this study to analyze the sleep architecture of SB and compare the sleep architecture of SB comorbid with different severities of OSAHS. Results Compared with the control group，the SB group had a younger age，increases in N1（%TST）and N2（%TST），a reduction in N3（%TST），and an increase in arousal index. The SB group was divided into non-OSAHS group（group 1），mild OSAHS group（group 2），and moderate-to-severe OSAHS group（group 3）. Group 1 had a younger age than group 2 and group 3，and group 3 had increases in body mass index（BMI），N1（%TST），oxygen desaturation index（ODI），and arousal index and a reduction in N3（%TST）. The Spearman's rank correlation analysis showed that BMI，N1（%TST），arousal index，and ODI increased with the increase in apnea-hypopnea index（AHI），while N3（%TST）decreased with the increase in AHI. The binary logistic regression analysis showed that SB was negatively correlated with age and was positively correlated with arousal index. Conclusion SB may affect sleep architecture by increasing light sleep，reducing deep sleep，and increasing the number of awakenings. There are changes in sleep architecture in case of SB comorbid with different severities of OSAHS. SB is negatively correlated with age and is positively correlated with arousal index.
Polysomnography

BACKGROUND

Dengue is a global health concern, particularly in tropical regions such as the Philippines. In 2019,Cebu City reported the highest number of dengue cases in Central Visayas with 3,290 cases and 20 deaths, an 11.8% increase compared to 20181 . To help predict disease outcomes and provide timely management, a scoring system, the Daily Dengue Severity Score (DDSS)² was utilized.

To determine the clinicodemographic profile of dengue patients, determine the accuracy of the DDSS in assessing disease severity, and determine a cut off score that suggests severe dengue.

Patients 1 month to 18 years admitted for dengue at Perpetual Succour Hospital from January 2018 to December 2020 were included. Cases were classified as Dengue without Warning Signs, Dengue with Warning Signs, and Severe Dengue, and scored using the DDSS. Statistical analysis used were Geometric mean and Area Under the Receiver Operating Characteristic (AUROC) curves to analyze the discriminative performance of the DDSS among the different disease severity states.

Out of 327 cases, 34 were classified as Dengue without Warning Signs, 271 Dengue with Warning Signs, and 22 Severe Dengue. The highest mean DDSS was 17.7 ±14.0 at Day -4 among those with Severe Dengue, and the lowest mean DDSS was 1.1 ± 2.0 at Day +3 among those with Dengue without Warning Signs. A cut off point of 10 on Day -1 predicted subsequent Severe Dengue among patients with Dengue with Warning Signs. In 91.39% of cases, there was a significant relationship between the DDSS and dengue classification, and the higher the DDSS, the more severe the disease.

Majority of dengue patients were males, aged 8.1 to 9.2 years. DDSS showed 66.67% sensitivity, 92.86% specificity, a positive likelihood ratio of 9.3, and a cutoff of 10 is predictive of severe dengue among patients with dengue with warning signs.

BACKGROUND

Diabetes Mellitus Type 2 is a significant global health issue with a high prevalence in the Philippines. Managing this condition effectively is crucial, and digital technologies, particularly smartphone (mHealth) applications, have emerged as a potential tool in diabetes self-management.

This study evaluated the effectiveness of smartphone (mHealth) application use in achieving glycemic control among adults with Type 2 Diabetes Mellitus, focusing on HbA1c levels and medication adherence.

This systematic review and meta-analysis, adhering to PRISMA guidelines, analyzed randomized controlled trials from databases like PubMed and Embase, comparing interventions using mHealth applications with standard care. The primary measures were HbA1c levels and medication adherence.

Ten studies involving 20,984 participants were included in the meta-analysis. Using mHealth applications led to an average HbA1c reduction of 0.36%, indicating improved glycemic control. There was considerable heterogeneity (I2 = 91%) because of the clinical and methodological diversity of the included studies. Subgroup analysis showed that the younger and older age groups, shorter and longer T2DM duration, and lower and higher HbA1c baseline benefited from its use. Sensitivity analysis still showed high heterogeneity (95%-97%), reflecting clinical diversity. A narrative analysis of two studies highlighted the utility of mHealth applications in tracking diet, physical activity, and vital stats, aiding medication adherence through reminders and data sharing with healthcare providers.

This systematic review and meta-analysis showed the effectiveness of mHealth application use in achieving glycemic control among adults with Type 2 Diabetes Mellitus by improving HbA1c levels and medication adherence. Integrating mHealth applications as adjuncts in family and community medicine as part of personalized care for managing type 2 diabetes in the Philippines can help achieve glycemic control and medication adherence. Future studies should focus on longitudinal assessments, exploring cultural and linguistic factors in the Filipino context to optimize diabetes care within this specialized medical framework.

Objective To investigate the differences in sleep structure and executive function between the patients with insomnia disorder and the individuals with normal sleep， as well as the potential mechanism of executive dysfunction in patients with insomnia disorder.Methods The patients with insomnia disorder who attended the outpatient service of Sleep Medicine Center， Chongqing Western Hospital， from March 2022 to December 2023 were enrolled as insomnia disorder group， and the individuals with normal sleep were enrolled as control group. All subjects were evaluated using Hamilton Anxiety Scale （HAMA）， Hamilton Depression Scale （HAMD）， polysomnography， and Stroop Color-Word Test. The two groups were compared in terms of anxiety， depression， sleep parameters （sleep latency， total sleep time， sleep efficiency， NREM1 and its percentage， NREM2 and its percentage， NREM3 and its percentage，as well as REM and its percentage）， executive function （time consumption and correct number of Stroop A，Stroop B，Stroop C， and interference test）， and a correlation analysis was also performed.Results There were 51 subjects in the insomnia disorder group and 25 subjects in the control group. Compared with the control group， the insomnia disorder group had significantly higher HAMA score， HAMD score， sleep latency， percentage of NREM1， and percentage of NREM2 （P<0.05）. Compared with the control group， the insomnia disorder group had significantly lower total sleep time， sleep efficiency， NREM3 duration， REM duration， and percentage of NREM3 （P<0.05）. Compared with the control group， the insomnia disorder group had significantly higher time consumption of Stroop Color-Word Test C and interference test （P<0.05）. In the insomnia disorder group， time consumption of Stroop C and interference test was negatively correlated with NREM3 duration and the percentage of NREM3 and was positively correlated with NREM2 duration and the percentage of NREM2， and time consumption of Stroop C was positively correlated with the percentage of NREM1（P<0.05）.Conclusion Patients with insomnia disorder tend to have a long sleep latency， a short total sleep time， low sleep efficiency，and reductions in deep sleep and executive function， and the reduction in executive function is associated with the reduction in slow-wave sleep.
Polysomnography

Objective: The aim of this study was to determine the comorbid sleep disorders on Polysomnography (PSG) of patients complaining of insomnia symptoms. Methodology: This is a retrospective study among patients who underwent diagnostic and split-night polysomnography from April 2014 to February 2019. Those who had at least one of the following insomnia symptoms of difficulty initiating sleep, difficulty maintaining sleep and early morning awakening with or without a history of sleep aide use were identified as patients with insomnia. Polysomnography sleep parameters and outcome were tabulated and statistical analysis was done using SPSS v 20.0. Results: Out of the 302 patients who were included in the study, 34.4% of subjects had a family history of sleep disorder and 70.4% had a history of sleep aide use. Among the medical comorbidities, 47.7% of the subjects were diagnosed with hypertension while 10.65% were diagnosed with psychiatric disorder. Most of the patients complained of both difficulty initiating sleep and early morning awakening. PSG sleep parameters showed that patients did not experience excessive daytime sleepiness or delayed sleep latency. On the other hand, poor sleep efficiency could be due to increased arousal index. Half of the patients turned out to have severe obstructive sleep apnea (52%) while 2.3% of the patients had periodic limb movement disorder. Among those diagnosed with severe OSA, 53.3% had a history of sleep aide use. Conclusion The study showed the importance of screening patients with insomnia for underlying comorbid sleep disorders. The American Academy of Sleep Medicine (AASM) treatment guidelines for chronic insomnia emphasized the need to have a high index of suspicion for this population in order to recommend diagnostic procedures such as polysomnography. Diagnosing a patient with insomnia to have an underlying sleep apnea and/or periodic limb movement disorder would change the course of management among patients with chronic insomnia and eventually avoid prescribing medications that could actually worsen the patient’s condition.
Sleep Initiation and Maintenance Disorders ; Sleep Wake Disorders ; Polysomnography ; Comorbidity

This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyle-induced diseases currently account for a significant portion of all healthcare spending, with this proportion projected to increase with population aging. Wearable devices have emerged as a key technology for implementing large-scale healthcare systems focused on disease prevention and management. Advancements in miniaturized sensors, system integration, the Internet of Things, artificial intelligence, 5G, and other technologies have enabled wearable devices to perform high-quality measurements comparable to medical devices. Through various physical, chemical, and biological sensors, wearable devices can continuously monitor physiological status information in a non-invasive or minimally invasive way, including electrocardiography, electroencephalography, respiration, blood oxygen, blood pressure, blood glucose, activity, and more. Furthermore, by combining concepts and methods from complex systems and nonlinear dynamics, we developed a novel theory of continuous dynamic physiological signal analysis-dynamical complexity. The results of dynamic signal analyses can provide crucial information for disease prevention, diagnosis, treatment, and management. Wearable devices can also serve as an important bridge connecting doctors and patients by tracking, storing, and sharing patient data with medical institutions, enabling remote or real-time health assessments of patients, and providing a basis for precision medicine and personalized treatment. Wearable devices have a promising future in the healthcare field and will be an important driving force for the transformation of the healthcare system, while also improving the health experience for individuals.
Humans ; Artificial Intelligence ; Wearable Electronic Devices ; Monitoring, Physiologic/methods*

Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients' cardiopulmonary function, and management of patients outside hospital.
Humans ; Artificial Intelligence ; Internet of Things ; Wearable Electronic Devices ; Monitoring, Physiologic/methods* ; Electrocardiography ; Internet

The aging population and the increasing prevalence of chronic diseases in the elderly have brought a significant economic burden to families and society. The non-invasive wearable sensing system can continuously and real-time monitor important physiological signs of the human body and evaluate health status. In addition, it can provide efficient and convenient information feedback, thereby reducing the health risks caused by chronic diseases in the elderly. A wearable system for detecting physiological and behavioral signals was developed in this study. We explored the design of flexible wearable sensing technology and its application in sensing systems. The wearable system included smart hats, smart clothes, smart gloves, and smart insoles, achieving long-term continuous monitoring of physiological and motion signals. The performance of the system was verified, and the new sensing system was compared with commercial equipment. The evaluation results demonstrated that the proposed system presented a comparable performance with the existing system. In summary, the proposed flexible sensor system provides an accurate, detachable, expandable, user-friendly and comfortable solution for physiological and motion signal monitoring. It is expected to be used in remote healthcare monitoring and provide personalized information monitoring, disease prediction, and diagnosis for doctors/patients.
Humans ; Aged ; Monitoring, Physiologic/methods* ; Wearable Electronic Devices ; Chronic Disease

Despite declines in morbidity and mortality in recent years, ischemic stroke (IS) remains one of the leading causes of death and disability from cerebrovascular diseases. Addressing the controllable risk factors underpins the successful clinical management of IS. Hypertension is one of the most common treatable risk factors for IS and is associated with poor outcomes. Ambulatory blood pressure monitoring has revealed that patients with hypertension have a higher incidence of blood pressure variability (BPV) than those without hypertension. Meanwhile, increased BPV has been identified as a risk factor for IS. The risk of IS is higher and the prognosis after infarction is worse with higher BPV, no matter in the acute or subacute phase. BPV is multifactorial, with alterations reflecting individual physiological and pathological changes. This article reviews the current research advances in the relationship between BPV and IS, with an attempt to raise awareness of BPV among clinicians and IS patients, explore the increased BPV as a controllable risk factor for IS, and encourage hypertensive patients to control not only average blood pressure but also BPV and implement personalized blood pressure management.
Humans ; Blood Pressure/physiology* ; Ischemic Stroke/complications* ; Blood Pressure Monitoring, Ambulatory ; Hypertension ; Stroke/complications* ; Prognosis