Objective To explore the prevalence of Helicobacter pylori (Hp) infection and its association with dietary and lifestyle habits among the adult physical examination population in Xuzhou area. Methods Retrospectively selected the physical examination population who underwent HP testing at our hospital's physical examination center from May 2021 to December 2023 as the research object. The prevalence of Hp infection in the population was analyzed based on the physical examination results. A questionnaire survey was used to collect information on the eating and living habits of all study subjects. Logistic regression was used to analyze the relationship between eating and living habits and Hp infection. Results A total of 1 354 physical examination people were included in the study, and the Hp infection rate was 37.30% (505/1354). The difference in Hp infection rates among people of different age groups is statistically significant (P<0.05), with the middle-aged population (41-59 years old) having the highest Hp positive infection rate (45.38%).High salt (41.11%), hot diet (40.56%), history of smoking (45.23%) and drinking (43.80%), less consumption of fruits and vegetables (43.73%), irregular exercise (41.29%), irregular diet People who frequently eat out (43.56%) and eat out frequently (42.57%) have a higher Hp infection rate (P<0.05).After adjusting for demographic factors such as gender, age, place of residence and education level, multivariate Logistic regression results showed that high-salt diet (OR=3.975, 95%CI: 2.670-5.917) and hot diet (OR=3.357, 95%CI: 2.291-4.919), smoking (OR=1.458, 95%CI: 1.082-1.964), drinking alcohol (OR=1.654, 95%CI: 1.279-2.138), eating fruits and vegetables (OR=1.759, 95%CI: 1.345-2.301), regular exercise (OR=1.822, 95%CI: 1.371-2.421), regular diet (OR=1.893, 95%CI: 1.391-2.575), eating out (OR=1.690, 95%CI: 1.277-2.237) were associated with the risk of Hp infection (P<0.05). Conclusion The positive infection rate of Hp among the physical examination population in Xuzhou is slightly lower than the average epidemic level in China. Cultivating healthy eating and living habits can effectively reduce the risk of Hp infection.

Objective To compare the differences in the average transaction costs per-referral patients under different models of Integrated Delivery Systems(IDS).Methods Using a typical case sampling method,it selected referred patients from three IDS models:the county medical alliance in D City(Qinghai Province),the urban medical consortium in J District(Zhengzhou City,Henan Province),and the health management coalition in N County(Shandong Province).Structured questionnaires collected demographics,average transaction costs per-referral and cost perceptions.t-tests and ANOVA assessed cost differences;generalized linear regression identified influencing factors.Results Among 915 patients,the average transaction costs per-referral were 1 035.05 yuan(county alliance),195.31 yuan(urban consortium),and 700.97 yuan(health management coalition),with statistically significant differences(P＜0.05).The urban consortium exhibited lower time costs and specialized input costs.Key influencing factors included older age(county alliance),education level,employment status,and referral travel time(urban consortium),as well as urban-rural disparities(health management coalition).Patients'cost perceptions significantly differed across models(P＜0.05).Conclusion The urban medical consortium demonstrated the lowest patient the average transaction costs,highlighting its institutional advantage in minimizing financial burdens.

ln the context of the high-quality development of public hospitals,research management is transitioning from a results-oriented approach to a full-process management model,necessitating the exploration of a governance system that integrates topic guidance,process support,and outcome transformation.Based on the Knowledge-to-Action and SECl model,it analyzes the construction logic and application effectiveness of the nursing research rounds mechanism at a teritary grade A hospital in Hainan Province.Through a"three-tier stratification+dual-track collaboration+full-process closed-loop"design,the mechanism bridges the chain from"clinical problem identification to research path optimization to outcome transformation",significantly enhancing research participation,research plan standardization,and research output.The findings validate the practical value of the research rounds mechanism in promoting knowledge transformation,capability enhancement,and organizational knowledge retention.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective Focusing on the problems of unbalanced nursing education resources and insufficient training,it discusses the path of nursing echelon training and nursing education resources optimization in secondary hospitals.Methods Based on nursing questionnaire,interview data and platform logs from 4 secondary hospitals in Hainan Province,Latent Dirichlet Allocation topic modeling,sentiment analysis and Social Network Analysis were used.Identify the core problems of educational resources and training system and propose optimization schemes.Results Topic modeling revealed that insufficient educational resources and information silos were major obstacles to shared platform development.Similarity analysis result showed high consistency in feedback regarding disconnected training content and single training models.Sentiment analysis result indicated that 50％of negative feedback focused on inadequate evaluation and incentive mechanisms.Social Network Analysis validated the significant role of multi-node collaboration in optimizing resource flows.Conclusion Building shared platforms,implementing differentiated training systems,and developing localized nursing faculty are critical pathways to achieving homogenized nursing education,providing valuable references for optimizing regional nursing education.

Objective Focusing on the problems of unbalanced nursing education resources and insufficient training,it discusses the path of nursing echelon training and nursing education resources optimization in secondary hospitals.Methods Based on nursing questionnaire,interview data and platform logs from 4 secondary hospitals in Hainan Province,Latent Dirichlet Allocation topic modeling,sentiment analysis and Social Network Analysis were used.Identify the core problems of educational resources and training system and propose optimization schemes.Results Topic modeling revealed that insufficient educational resources and information silos were major obstacles to shared platform development.Similarity analysis result showed high consistency in feedback regarding disconnected training content and single training models.Sentiment analysis result indicated that 50％of negative feedback focused on inadequate evaluation and incentive mechanisms.Social Network Analysis validated the significant role of multi-node collaboration in optimizing resource flows.Conclusion Building shared platforms,implementing differentiated training systems,and developing localized nursing faculty are critical pathways to achieving homogenized nursing education,providing valuable references for optimizing regional nursing education.

Objective To compare the differences in the average transaction costs per-referral patients under different models of Integrated Delivery Systems(IDS).Methods Using a typical case sampling method,it selected referred patients from three IDS models:the county medical alliance in D City(Qinghai Province),the urban medical consortium in J District(Zhengzhou City,Henan Province),and the health management coalition in N County(Shandong Province).Structured questionnaires collected demographics,average transaction costs per-referral and cost perceptions.t-tests and ANOVA assessed cost differences;generalized linear regression identified influencing factors.Results Among 915 patients,the average transaction costs per-referral were 1 035.05 yuan(county alliance),195.31 yuan(urban consortium),and 700.97 yuan(health management coalition),with statistically significant differences(P＜0.05).The urban consortium exhibited lower time costs and specialized input costs.Key influencing factors included older age(county alliance),education level,employment status,and referral travel time(urban consortium),as well as urban-rural disparities(health management coalition).Patients'cost perceptions significantly differed across models(P＜0.05).Conclusion The urban medical consortium demonstrated the lowest patient the average transaction costs,highlighting its institutional advantage in minimizing financial burdens.

ln the context of the high-quality development of public hospitals,research management is transitioning from a results-oriented approach to a full-process management model,necessitating the exploration of a governance system that integrates topic guidance,process support,and outcome transformation.Based on the Knowledge-to-Action and SECl model,it analyzes the construction logic and application effectiveness of the nursing research rounds mechanism at a teritary grade A hospital in Hainan Province.Through a"three-tier stratification+dual-track collaboration+full-process closed-loop"design,the mechanism bridges the chain from"clinical problem identification to research path optimization to outcome transformation",significantly enhancing research participation,research plan standardization,and research output.The findings validate the practical value of the research rounds mechanism in promoting knowledge transformation,capability enhancement,and organizational knowledge retention.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To construct a classification model for endoscopic ultrasonography (EUS) images of gastrointestinal stromal tumors (GISTs) and leiomyomas (LM) based on deep learning technology, and to verify its value for differential diagnosis.Methods:From October 2014 to October 2021, 69 patients of GISTs and 73 of LM who underwent EUS and were pathologically confirmed by surgery or endoscopic resection in the Second Affiliated Hospital of Soochow University were retrospectively studied. One clear EUS image with typical lesion was selected for each case. Using the hold-out method, the images of each disease were divided into the training set and the validation set according to the ratio of the number of images in the training set to the number of images in the validation set, which was 8∶2. Finally, 113 EUS images (55 GISTs and 58 LM) were used to form the training set, and 29 EUS images (14 GISTs and 15 LM) were used to form the validation set. The training set was used to train and optimize the deep learning model, and the validation set was used to verify the classification model. The main observation indicators included the sensitivity, the specificity, the positive predictive value, the negative predictive value and the accuracy of differential diagnosis.Results:The accuracy of the classification model established by Resnet 34 network structure in the differential diagnosis of GISTs and LM tended to be 0.89, better than the classification model established by Resnet 50 network structure (0.81). The sensitivity, the specificity, the positive predictive value, the negative predictive value and the accuracy of the classification model based on Resnet 34 network structure for differentiating EUS images in the validation set were 85.71% (12/14, 95% CI: 67.38%-100.00%), 93.33% (14/15, 95% CI: 80.71%-100.00%), 92.31% (12/13, 95% CI: 77.82%-100.00%), 87.50% (14/16, 95% CI: 71.30%-100.00%) and 89.66% (26/29, 95% CI: 78.57%-100.00%), respectively. Conclusion:It is feasible to use deep learning technology in the differential diagnosis of EUS images of GISTs and LM, which can provide auxiliary diagnostic opinions for clinicians. The deep learning model based on Resnet 34 network structure shows higher accuracy in the differential diagnosis of EUS images of GISTs and LM.