[Nomographic Model for Predicting Severe Foot Pain in Nurses from Tertiary Hospitals in China].

Objective: To investigate the prevalence and common sites of severe foot pain among nurses, to define the risk factors of severe foot pain in nurses in tertiary hospital in China, and to construct a nomograph model for predicting individuals' risks for severe foot pain. Methods: Between August 2019 and December 2019, a stratified global sampling method was used to select 10691 nurses from 351 tertiary hospitals in China to investigate the incidence of severe foot pain among them. The variables that may affect the occurrence of severe foot pain were analyzed by single factor analysis to identify the influencing factors of severe foot pain in nurses. Furthermore, the independent risk factors of severe foot pain were analyzed by stepwise logistic regression analysis. The statistically significant factors identified in the multivariate regression analysis were incorporated into the nomograph prediction model. The predictive performance of the nomograph was measured by the consistency index (C-index) and calibrated with 1000 Bootstrap samples. Results: A total of 3419 nurses out of the 10691 had foot pain, resulting in an incidence of 31.98%. The incidence of severe pain (VAS score 7-10) was 2.27% (243 of 10691). The locations of severe pain were more commonly found in the soles and heels of both feet. Six factors, including age, education, the material of the work shoes, comfortableness of the work shoes, number of complications, and foot injure history, were incorporated in the nomograph predicting model. The C-index value was 0.706 and the standard curve fitted well with the calibrated prediction curve. Conclusion: The risk prediction model constructed in this study showed sound performance in predicting the risk of severe foot pain in nurses, and all the indicators involved are simple and the relevant data are easily obtained. The model can provide reference for preventing severe foot pain in nurses.

A brief discussion on evidence-based clinical research of traditional Chinese medicine.

BACKGROUND: The evaluation of clinical efficacy of traditional Chinese medicine (TCM) is the focus of the development of Chinese medicine, but at present there is no internationally recognized clinical efficacy evaluation system, which prevents TCM going abroad. Evidence-based medicine (EBM) research methods have achieved good results in the evaluation of TCM, but there are still some problems. How to use EBM methods in accordance with China's national conditions and develop evidence-based TCM that meets its own characteristics is the key to the current discussion. METHODS: Search websites such as PubMed, China National Knowledge Infrastructure, Wanfang Data and VIP by computer, and search papers related to evidence-based clinical research of TCM. RESULTS: A total of 15 high quality representative research papers published in internationally renowned journals were selected for example, including 4 randomized controlled trials (RCTs) related to Chinese medicine, 9 RCTs related to acupuncture, and 2 observational studies on the safety of TCM. CONCLUSIONS: EBM method is suitable for clinical research of TCM. There are differences between "disease" and "syndromes" in the use of TCM. Based on the further standardization of syndromes and classification of TCM, modern clinical research methods can be reasonably applied. However, the quality of clinical research related to TCM is not high, and there is a lack of research related to the safety of it, which should be paid attention to and improved in future research.