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.

Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.
Humans ; Blood Glucose ; Blood Glucose Self-Monitoring/methods* ; Diabetes Mellitus/diagnosis* ; Monitoring, Physiologic/methods* ; Tears

OBJECTIVE: To retrieve the evidence for threshold setting of multi-parameter electrocardiograph (ECG) monitors in intensive care unit (ICU), and summarize the best evidence. METHODS: After literature retrieval, clinical guidelines, expert consensus, evidence summary and systematic review that met the requirements were screened. Guidelines were evaluated by the appraisal of guidelines for research and evaluation II (AGREE II), expert consensus and systematic review were evaluated by the Australian JBI evidence-based health care center authenticity evaluation tool, and evidence summary was evaluated by the CASE checklist. High-quality literature was selected to extract evidence related to the use and setup of multi-parameter ECG monitors in the ICU. RESULTS: A total of 19 literatures were included, including 7 guidelines, 2 expert consensus, 8 systematic reviews, 1 evidence summary, and 1 national industry standard. After evidence extraction, translation, proofreading and summary, a total of 32 pieces of evidence were integrated. The included evidence involved the environmental preparation for the application of the ECG monitor, the electrical requirements of the ECG monitor, ECG monitor use process, ECG monitor alarm setting principles, ECG monitor alarm heart rate or heart rhythm monitoring setting, ECG monitor alarm blood pressure monitoring setting, ECG monitor alarm respiratory and blood oxygen saturation threshold setting, alarm delay warning time setting, adjusting alarm setting method, evaluating alarm setting time, improving the comfort of monitoring patients, reducing nuisance alarm report the occurrence, alarm priority processing, alarm intelligent processing and so on. CONCLUSIONS This summary of evidence involves many aspects of the setting and application of ECG monitor. According to the latest guidelines and expert consensus, it is updated and revised to guide healthcare workers to monitor patients more scientifically and safely, and aims to ensure patient safety.
Humans ; Clinical Alarms ; Australia ; Intensive Care Units ; Arrhythmias, Cardiac ; Electrocardiography ; Monitoring, Physiologic

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

OBJECTIVE: Reduce the number of false alarms and measurement time caused by movement interference by the sync waveform of the movement. METHODS: Vital signal monitoring system based on motion sensor was developed, which collected and processed the vital signals continuously, optimized the features and results of vital signals and transmitted the vital signal results and alarms to the interface. RESULTS: The system was tested in many departments, such as digestive department, cardiology department, internal medicine department, hepatobiliary surgery department and emergency department, and the total collection time was 1 940 h. The number of false electrocardiograph (ECG) alarms decreased by 82.8%, and the proportion of correct alarms increased by 28%. The average measurement time of non-invasive blood pressure (NIBP) decreased by 16.1 s. The total number of false respiratory rate measurement decreased by 71.9%. CONCLUSIONS False alarms and measurement failures can be avoided by the vital signal monitoring system based on accelerometer to reduce the alarm fatigue in clinic.
Humans ; Monitoring, Physiologic ; Electrocardiography ; Arrhythmias, Cardiac ; Blood Pressure ; Accelerometry ; Clinical Alarms

In view of the high incidence of malignant diseases such as malignant arrhythmias in the elderly population, accidental injuries such as falls, and the problem of no witnesses when danger occurs, the study developed a human vital signs and body posture monitoring and positioning alarm system. Through the collection and analysis of electrocardiogram (ECG), respiration (RESP) and acceleration (ACC) signals, the system monitors human vital signs and body posture in real time, automatically judges critical states such as malignant arrhythmias and accidental falls on the local device side, and then issues alarm information, opens the positioning function, and uploads physiological information and patient location information through 4G communication. Experiments have shown that the system can accurately determine the occurrence of ventricular fibrillation and falls, and issue position and alarm information.
Humans ; Aged ; Arrhythmias, Cardiac/diagnosis* ; Ventricular Fibrillation ; Electrocardiography ; Accidental Falls ; Vital Signs ; Posture ; Monitoring, Physiologic

OBJECTIVE: To investigate the clinical value of analgesia and sedation under bispectral index (BIS) monitoring combined with hydraulic coupled intracranial pressure (ICP) monitoring in severe craniocerebral injury (sTBI). METHODS: (1) A prospective self-controlled parallel control study was conducted. A total of 32 patients with sTBI after craniotomy admitted to the intensive care unit (ICU) of the First People's Hospital of Huzhou from December 2020 to July 2021 were selected as the research objects. ICP was monitored by Codman monitoring system and hydraulically coupled monitoring system, and the difference and correlation between them were compared. (2) A prospective randomized controlled study was conducted. A total of 108 sTBI patients admitted to the ICU of the First People's Hospital of Huzhou from August 2021 to August 2022 were selected patients were divided into 3 groups according to the random number table method. All patients were given routine treatment after brain surgery. On this basis, the ICP values of the patients in group A (35 cases) were monitored by Codman monitoring system, the ICP values of the patients in group B (40 cases) were monitored by hydraulic coupling monitoring system, and the ICP values of the patients in group C (33 cases) were monitored combined with hydraulic coupling monitoring system, and the analgesia and sedation were guided by BIS. The ICP after treatment, cerebrospinal fluid drainage time, ICP monitoring time, ICU stay time, complications and Glasgow outcome score (GOS) at 6 months after surgery were compared among the 3 groups. In addition, patients in group B and group C were further grouped according to the waveforms. If P₁ = P₂ wave or P₂ and P₃ wave were low, they were classified as compensatory group. If the round wave or P₂ > P₁ wave was defined as decompensated group, the GOS scores of the two groups at 6 months after operation were compared. RESULTS: (1) There was no significant difference in ICP values measured by Codman monitoring system and hydraulic coupling monitoring system in the same patient (mmHg: 11.94±1.76 vs. 11.88±1.90, t = 0.150, P = 0.882; 1 mmHg≈0.133 kPa). Blan-altman analysis showed that the 95% consistency limit (95%LoA) of ICP values measured by the two methods was -4.55 to 4.68 mmHg, and all points fell within 95%LoA, indicating that the two methods had a good correlation. (2) There were no significant differences in cerebrospinal fluid drainage time, ICP monitoring time, ICU stay time, and incidence of complications such as intracranial infection, intracranial rebleeding, traumatic hydrocephalus, cerebrospinal fluid leakage, and accidental extubation among the 3 groups of sTBI patients (P > 0.05 or P > 0.017). The ICP value of group C after treatment was significantly lower than that of group A and group B (mmHg: 20.94±2.37 vs. 25.86±3.15, 26.40±3.09, all P < 0.05), the incidence of pulmonary infection (9.1% vs. 45.7%, 42.5%), seizure (3.0% vs. 31.4%, 30.0%), reoperation (3.0% vs. 31.4%, 40.0%), and poor prognosis 6 months after operation (33.3% vs. 65.7%, 65.0%) were significantly lower than those in group A and group B (all P < 0.017). According to the hydraulic coupling waveform, GOS scores of 35 patients in the compensated group were significantly higher than those of 38 patients in the decompensated group 6 months after operation (4.03±1.18 vs. 2.39±1.50, t = 5.153, P < 0.001). CONCLUSIONS The hydraulic coupled intracranial pressure monitoring system has good accuracy and consistency in measuring ICP value, and it can better display ICP waveform changes than the traditional ICP monitoring method, and has better prediction value for prognosis evaluation, which can replace Codman monitoring to accurately guide clinical work. In addition, analgesia and sedation under BIS monitoring combined with hydraulic coupled ICP monitoring can effectively reduce ICP, reduce the incidence of complications, and improve the prognosis, which has high clinical application value.
Humans ; Intracranial Pressure ; Prospective Studies ; Monitoring, Physiologic/methods* ; Craniocerebral Trauma ; Analgesia ; Cerebrospinal Fluid Leak

Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.
Expert Systems ; Monitoring, Physiologic