There are already many ion detection methods available, and their development in long-term application practice has become very mature, which can achieve high-precision monitoring of different ion types and ion concentrations. However, in order to meet the requirements of modern smart healthcare, portable ion continuous monitoring methods with good portability, low operational difficulty, and high detection efficiency urgently need to be developed. However, existing detection methods are far from meeting the requirements of real-time and long-term health monitoring due to factors such as detection principles. In recent years, breakthroughs have been made in miniaturized and portable ion continuous monitoring technology, among which high-sensitivity and high-specificity miniature ion sensing components and miniaturized low-power driving measurement circuits have become the main research contents of this technology. This article starts with high-performance ion sensors in the front-end and high-level integrated driving measurement circuits in the back-end, summarizes the current development of miniaturized and portable ion continuous monitoring technology, reviews its applications, and looks forward to the possible development directions of portable ion monitoring technology in the future.
Objective
To investigate the method and effect of continuous improvement of adverse drug reaction (ADR) monitoring in a major public hospital’s cooperating branch hospital.
Methods
PDCA cycle management was used to continuously improve the quality of ADR monitoring. ADR report network platform was established in the fourth quarter of 2014; ADR report specification training for the medical personnel was held in the first quarter of 2015; a examine mechanism was built in the second quarter of 2015. The quality and quantity of ADR monitoring before and after the PDCA cycle management were analyzed.
Results
ADR report timeliness conform to the requirements increased from 45.5% (from the first to third quarter of 2014) to 98.1% (from the fourth quarter of 2014 to the second quarter of 2015); accurate ADR types checking, normal name writting, and complete process description increased from 68.6%, 65.7%, 8.6% (from January 2014 to Frequency 2015) to 92.9%, 96.4%, 85.7% (from March to June 2015); the quantity of ADR report was obviously improved.
Conclusion
Learning from public hospital’s experience and considering its own condition in ADR monitoring, cooperating branch hospital utilizes PDCA cycle management which could continuously improve the ADR monitoring.
Objective To compare the environmental microbiological and physical monitoring parameters between the temporary extended medical area and the normal area during the flexible allocation of ward, summarize the rule and find the potential risk points of infection control. Methods From April 10th to 23rd, 2023, prospective environmental microbial monitoring and physical parameter monitoring were carried out in a ward of Zhongnan Hospital of Wuhan University, and the monitoring results under different scenarios were compared and analyzed. Results In general, the carbon dioxide (CO2) concentration, particulate matter 2.5 (PM2.5) concentration, temperature, and relative humidity in the temporary medical area were better than those in the inpatient rooms (P<0.05), but there was no statistically significant difference in the amount of microorganisms detected on the surface of environmental objects or the hands of medical staff (P>0.05). After the start of the temporary medical area, the amount of microorganisms detected on the surface of environmental objects, CO2 concentration, and temperature in the inpatient rooms were higher than those in the temporary medical area (P<0.05), the PM2.5 concentration in the inpatient rooms was lower than that in the temporary medical area (P<0.05), and there was no statistically significant difference in the amount of microorganisms detected on the hands of medical staff or relative humidity between the two areas (P>0.05). Compared with those in the same area when the temporary medical area was not started, in the inpatient rooms after the start, the amount of microorganisms detected in the air, CO2 concentration, temperature, and relative humidity were lower (P<0.05), the amount of microorganisms detected on the surface of environmental objects and PM2.5 concentration were higher (P<0.05), and there was no statistically significant difference in the amount of microorganisms detected on the hands of medical staff between the two periods (P>0.05); in the temporary medical area after the start, the PM2.5 concentration was higher (P<0.05), the CO2 concentration and temperature were lower (P<0.05), and the differences in the relative humidity and amounts of microorganisms detected on the surface of environmental objects and the hands of medical staff between the two periods were not statistically significant (P>0.05). Regardless of whether the temporary medical area was activated or not, Filamentous fungi had the highest detection rates in air samples, and Staphylococcus epidermidis had the highest detection rates in both environmental surface samples and medical staff hand samples. Conclusion A series of environmental risks such as environmental microbial load and poor ventilation caused by temporary medical areas should be paid attention to.
ObjectiveTo systematically review the research status of therapeutic drug monitoring (TDM) for traditional Chinese medicine. MethodsPubMed, EMbase, The Cochrane Library, CNKI, WanFang Data, CBM, VIP databases, official websites of governments and societies associated with TDM were electronically searched to collect studies on TDM for traditional Chinese medicine from inception to January, 2022. Two reviewers independently screened literature and extracted data. Then, a qualitative systematic review was conducted. ResultsA total of 13 studies were included, all of which came from China and were small sample size studies. The studied population consisted mainly of healthy volunteers (85%), followed by patients of coronary artery disease with blood stasis pattern (31%), patients of rheumatoid arthritis (8%), and patients of acquired immune deficiency syndrome (8%). There were two types of medicine, including proprietary Chinese medicine (69%) and Chinese herbal pieces (31%). The research topics were all theoretical research of TDM, mainly concentration detection methods (77%), followed by influence factors of blood drug concentration (15%), the selection of specimen (15%), the selection of monitoring object (8%) and the concentration reference range (8%). There was no clinical practice study on TDM of traditional Chinese medicine. ConclusionTDM of traditional Chinese medicine is still in the exploratory stage in China. Published studies are mainly on the theoretical research of TDM, and no relevant studies is on clinical practice of TDM of traditional Chinese medicine.
This article aims to review the recall of refecoxib which increases the incidence of cardiovascular and cerebrovascular diseases and to find the methods to solve problems in post marked monitoring of drug safety.
ObjectiveTo investigate the incidence and trendency of healthcare-associated infections (HAIs) in a pediatric intensive care unit (ICU) of a hospital, identify the main objectives of infection control, and formulate corresponding preventive and control measures.MethodsA prospective targeted monitoring method was adopted to investigate HAIs in the pediatric ICU of a hospital from January 2013 to December 2018.ResultsFrom January 2013 to December 2018, the number of target ICU patients was 11 898, the number of patient-days was 55 159; 226 HAIs occurred, the HAI case rate was 1.90%, the incidence of HAI per 1 000 patient-days was 4.10‰, and the adjusted incidence of HAI per 1 000 patient-days was 1.21‰. The main infection site was respiratory tract [83 cases (36.7%)], with ventilator-associated pneumonia in 73 cases (32.3%); secondly, 69 patients (30.5%) had bloodstream infection, among which 48 (21.2%) had non-catheter-related bloodstream infection.ConclusionHospital targeted monitoring is helpful to grasp the situation and trend of HAIs, define the main target of infection control, and formulate corresponding preventive and control measures, which can effectively reduce the incidence of HAIs.
Since the concept of digital twin technology has been put forward, after decades of rapid development and wide application, it has not only made great achievements in many fields, but also brought broader prospects for the development of the medical field. As an important trend in the medical industry, digital twin hospitals play multiple roles by connecting physical hospitals and virtual hospitals and benefit the “patient-medical staff-hospital administrators”, highlighting the immeasurable promising application of digital twin technology in smart hospitals. This review takes digital twin technology as an entry point, briefly introduces the progress of its application in various fields, focuses on the characteristics of digital twin technology, practical application cases in hospitals and their limitations, and also looks forward to its future development prospects, aiming to provide certain useful insights and guidance for the future of digital twin hospitals, and also expecting it to play an important role in changing the future of healthcare to a certain extent.
Heart failure (HF) is the end-stage of all cardiac diseases, characterized by high prevalence, high mortality, and heavy social and economic burden. Early warning of HF exacerbation is of great value for outpatient management and reducing readmission rates. Currently, remote dynamic monitoring technology, which captures changes in hemodynamic and physiological parameters of HF patients, has become the primary method for early warning and is a hot research topic in clinical studies. This paper systematically reviews the progress in this field, which was categorized into invasive monitoring based on implanted devices, non-invasive monitoring based on wearable devices, and other monitoring technologies based on audio and video. Invasive monitoring primarily involves direct hemodynamic parameters such as left atrial pressure and pulmonary artery pressure, while non-invasive monitoring covers parameters such as thoracic impedance, electrocardiogram, respiration, and activity levels. These parameters exhibit characteristic changes in the early stages of HF exacerbation. Given the clinical heterogeneity of HF patients, multi-source information fusion analysis can significantly improve the prediction accuracy of early warning models. The results of this study suggest that, compared with invasive monitoring, non-invasive monitoring technology, with its advantages of good patient compliance, ease of operation, and cost-effectiveness, combined with AI-driven multimodal data analysis methods, shows significant clinical application potential in establishing an outpatient management system for HF.
Currently, monitoring system of awareness of the depth of anesthesia has been more and more widely used in clinical practices. The intelligent evaluation algorithm is the key technology of this type of equipment. On the basis of studies about changes of electroencephalography (EEG) features during anesthesia, a discussion about how to select reasonable EEG parameters and classification algorithm to monitor the depth of anesthesia has taken place. A scheme which combines time domain analysis, frequency domain analysis and the variability of EEG and decision tree as classifier and least squares to compute Depth of anesthesia Index (DOAI) is proposed in this paper. Using the EEG of 40 patients who underwent general anesthesia with propofol, and the classification and the score of the EEG annotated by anesthesiologist, we verified this scheme with experiments. Classification and scoring was based on a combination of modified observer assessment of alertness/sedation (MOAA/S), and the changes of EEG parameters of patients during anesthesia. Then we used the BIS index to testify the validation of the DOAI. Results showed that Pearson's correlation coefficient between the DOAI and the BIS over the test set was 0.89. It is demonstrated that the method is feasible and has good accuracy.
Aiming at the human-computer interaction problem during the movement of the rehabilitation exoskeleton robot, this paper proposes an adaptive human-computer interaction control method based on real-time monitoring of human muscle state. Considering the efficiency of patient health monitoring and rehabilitation training, a new fatigue assessment algorithm was proposed. The method fully combined the human neuromuscular model, and used the relationship between the model parameter changes and the muscle state to achieve the classification of muscle fatigue state on the premise of ensuring the accuracy of the fatigue trend. In order to ensure the safety of human-computer interaction, a variable impedance control algorithm with this algorithm as the supervision link was proposed. On the basis of not adding redundant sensors, the evaluation algorithm was used as the perceptual decision-making link of the control system to monitor the muscle state in real time and carry out the robot control of fault-tolerant mechanism decision-making, so as to achieve the purpose of improving wearing comfort and improving the efficiency of rehabilitation training. Experiments show that the proposed human-computer interaction control method is effective and universal, and has broad application prospects.
