Objective To understand the effect of World Health Organization(WHO) multimodal hand hygiene improvement strategy on hand hygiene compliance among acupuncturists. Methods All the acupuncturists in departments (Department of Acupuncture, Department of Encephalopathy, Department of Orthopedics and Traumatology) with acupuncture programs in Xi’an Hospital of TCM were chosen in this study between September 2015 and August 2016. Based on the WHO multimodal hand hygiene improvement strategy, comprehensive measures were regulated among acupuncturists. Hand hygiene compliance and accuracy, and hand hygiene knowledge score were compared before and after the strategy intervention. Then, the effects of key strategies were evaluated. Results Overall hand hygiene compliance rate, accuracy and knowledge scores increased from 51.07%, 19.86% and 81.90±2.86 before intervention to 72.34%, 51.70%, and 98.62±2.92 after intervention (P<0.05). Hand hygiene compliance rates also increased in various occasions such as before contacting the patient, after contacting the patient, before acupuncture treatment, and before acupuncture needle manipulation (P<0.05). Conclusion Hand hygiene compliance in acupuncturists can be significantly improved by the implementation of WHO multimodal hand hygiene improvement strategy.
Electrocardiogram (ECG) signals are easily disturbed by internal and external noise, and its morphological characteristics show significant variations for different patients. Even for the same patient, its characteristics are variable under different temporal and physical conditions. Therefore, ECG signal detection and recognition for the heart disease real-time monitoring and diagnosis are still difficult. Based on this, a wavelet self-adaptive threshold denoising combined with deep residual convolutional neural network algorithm was proposed for multiclass arrhythmias recognition. ECG signal filtering was implemented using wavelet adaptive threshold technology. A 20-layer convolutional neural network (CNN) containing multiple residual blocks, namely deep residual convolutional neural network (DR-CNN), was designed for recognition of five types of arrhythmia signals. The DR-CNN constructed by residual block local neural network units alleviated the difficulty of deep network convergence, the difficulty in tuning and so on. It also overcame the degradation problem of the traditional CNN when the network depth was increasing. Furthermore, the batch normalization of each convolution layer improved its convergence. Following the recommendations of the Association for the Advancements of Medical Instrumentation (AAMI), experimental results based on 94 091 2-lead heart beats from the MIT-BIH arrhythmia benchmark database demonstrated that our proposed method achieved the average detection accuracy of 99.034 9%, 99.498 0% and 99.334 7% for multiclass classification, ventricular ectopic beat (Veb) and supra-Veb (Sveb) recognition, respectively. Using the same platform and database, experimental results showed that under the comparable network complexity, our proposed method significantly improved the recognition accuracy, sensitivity and specificity compared to the traditional deep learning networks, such as deep Multilayer Perceptron (MLP), CNN, etc. The DR-CNN algorithm improves the accuracy of the arrhythmia intelligent diagnosis. If it is combined with wearable equipment, internet of things and wireless communication technology, the prevention, monitoring and diagnosis of heart disease can be extended to out-of-hospital scenarios, such as families and nursing homes. Therefore, it will improve the cure rate, and effectively save the medical resources.
The essence of ensuring universal nutritional health lies in achieving a balance between the growing demand for nutritional health and the supply of adequate and balanced nutritional services. This paper learns and draws on the ideological theory and methodological support of evidence-based science, optimizing practices, reevaluations, monitoring risks, producing evidence and cultivating talents so as to enable the interdisciplines of evidence-based nutrition and develop in a localized way and gain optimal timeliness, quantity and quality.
Knowledge translation (KT) provides a paradigm to bridge the gap between knowledge and practice, which has critical instructive significance for health promotion. This article expounds on the connotation of KT by comparing it with similar terms. Next, it introduces three kinds of common KT theoretical models, including process models, determinant frameworks, and evaluation frameworks. Finally, its application and experiences in health promotion are summarized to provide references for the ongoing health promotion in China.
Objective To investigate the current status of health promoting lifestyle in maintenance hemodialysis (MHD) patients and to explore its correlation with chronic illness resource utilization. Methods Patients who underwent outpatient MHD in the Hemodialysis Room of the Department of Nephrology, West China Hospital, Sichuan University between January and March 2023 were selected. Patients were surveyed using the General Information Questionnaire, Chronic Illness Resource Survey, and Health Promoting Lifestyle Profile-Ⅱ Revise. Results A total of 158 patients were surveyed. MHD patients scored 103.37±18.52 on health promoting lifestyle, and 68.95±14.14 on chronic illness resource utilization. The Pearson correlation analysis results showed that there was a positive correlation between the chronic illness resource utilization and the total score of health promoting lifestyle in MHD patients (r=0.765, P<0.001), as well as scores in all dimensions (P<0.05). The results of multiple linear regression analysis showed that the main caregivers being parents [non-standardized partial regression coefficient (b)=8.150, 95% confidence interval (CI) (0.804, 15.497), P=0.030], weekly dialysis times [b=10.701, 95%CI (2.787, 18.615), P=0.008], and chronic illness resource utilization [b=0.936, 95%CI (0.800, 1.072), P<0.001] were influencing factors for health promoting lifestyle. Conclusions MHD patients have an average health promoting lifestyle, and ideal chronic illness resource utilization. Hemodialysis nurses can take targeted measures to enhance chronic illness resource utilization and health promoting lifestyle in MHD patients, which can further improve the quality of life of MHD patients.