Epigastric pain, the most common symptom of chronic pancreatitis (CP), seriously affects the quality of life and causes huge social and economic burden. The pathogenesis of pain involves pancreatic duct hypertension, neurogenic mechanisms, and the effects of inflammatory mediators. As a minimally invasive treatment, endoscopic therapy has emerged as a pivotal option for pain treatment in CP, primarily encompassing pancreatic duct decompression techniques and nerve interventions under endoscopy. Endoscopic pancreatic duct decompression, based on endoscopic retrograde cholangiopancreatography (ERCP) and combined with extracorporeal shock wave lithotripsy (ESWL), can effectively reduce pancreatic duct pressure and relieve pain through pancreatic duct stone removal and main pancreatic duct stent implantation. Endoscopic nerve intervention techniques mainly include celiac plexus block/neurolysis and radiofrequency ablation under the guidance of endoscopic ultrasonography (EUS), which can relieve pain by inhibiting nociceptive transmission or destroying nerve fibers. This article reviewed the mechanism of CP abdominal pain and the progress of endoscopic treatment.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Epidemiology and medical statistics are essential courses for undergraduate students majoring in clinical medicine. By studying the two courses, they can obtain the core skills for their future clinical practice. High-level medical schools both at home and abroad have accumulated successful experiences in curriculum, teaching methods and teaching models of the two disciplines. These colleges have also carried out the exploration of the curriculum reform centering on "organ systems integration". This paper summarizes the current status of epidemiology and medical statistics teaching and curriculum integration in representative medical schools both at home and abroad, and puts forward suggestions for deepening teaching reform and optimizing the curriculum system to provide reference for the integration of epidemiology and medical statistics curriculums for undergraduate students majoring in clinical medicine in China.

Established in 2017, the Screening Cohort for Asian Nomadic descendants in China (Scan-China) has benefited over 180,000 members of a multi-ethnic population, particularly individuals of Mongolian descent compared with the general population (Han ethnicity), in the Inner Mongolia Autonomous Region, China. This cohort study aims to evaluate the effectiveness of cancer screening and serve as a real-world data platform for cancer studies. The 6 most prevalent cancers in China are considered—namely, breast, lung, colorectal, gastric, liver and esophageal cancer. After baseline cancer risk assessments and screening tests, both active and passive follow-up (based on the healthcare insurance database, cancer registry, the front page of hospital medical records, and death certificates) will be conducted to trace participants’ onset and progression of cancers and other prevalent chronic diseases. Scan-China has preliminarily found a disproportionately lower screening participation rate and higher incidence/mortality rates of esophageal and breast cancer among the Mongolian population than among their Han counterparts. Further research will explore the cancer burden, natural history, treatment patterns, and risk factors of the target cancers.

Humans ; Non-alcoholic Fatty Liver Disease ; Prospective Studies ; Risk Factors ; Exercise ; Liver

Adjusting time-dependent covariates into prediction models may help improve model performance and expand clinical applications. The methodology of handling time-dependent covariates is limited in traditional regression strategies (i.e., landmark model, joint model). For example, the number of predictors and practical situations which can be handled are restricted when using regression models. One new strategy is to use machine learning (i.e., neural networks). This review summarizes the methodology of handling time-dependent covariates in prediction models, such as applicable scenarios, strengths, and limitations, to offer methodological enlightenment for processing time-dependent covariates.

Objective To establish the key question list for the development of evidencebased guideline in China according to the content and limitation of current evidence-based guidelines around the world.Methods First,we introduced the evidence-based guidelines in detail which met the criteria based on World Health Organization guideline development handbook and then formulated the draft list of key questions for the development of evidence-based guidelines.At last,the Delphi method was used to determine the list of key questions in developing evidence-based guidelines of colorectal cancer screening.Results Totally,34 questionnaires were collected,with experts from clinical and epidemiological fields.The average experts' authority coefficient was 0.81,indicating a high degree of authority.The concentration of opinions on all items in the questionnaire was relatively high,with the full score ratio greater than 75％ and the coefficient of variation less than 0.3.The list of key questions on evidence-based guidelines for colorectal cancer screening has been divided into six parts:epidemiological problems,risk classification,screening age,screening tools,implementation and selection of steering group members,which covers the issues that need to be considered in the development of evidence-based colorectal cancer screening guidelines in China.Conclusion The key question list for evidence-based guideline development in our study can be applied to the development of evidence-based guidelines for colorectal cancer screening in the future,as well as the development of evidence-based guidelines for other cancer screening in China.

Objective:The objective of the study was systematically summarized the current status of the hepatocellular carcinoma (HCC) screening guidelines, and evaluated the HCC screening guidelines according to the authoritative framework of cancer screening guidelines of authoritative institutions, which provided important value for the formulation of HCC screening evidence-based guidelines.Methods:Literature search was conducted in multiple databases from their inception dates to January 3, 2019. In addition, we sought relevant websites further was searched to identify potentially eligible studies. Two reviewers independently screened literature and extracted data. Qualitative description of the basic information, recommendations of HCC screening, source of evidence and update progress of the HCC screening guidelines was conducted.Results:At present, there were no independent HCC screening guidelines worldwide. There were only 17 clinical practice HCC guidelines briefly provided the recommendation of HCC screening. Current HCC screening guidelines only recommended screening for high-risk groups of HCC. All guidelines have identified patients with chronic hepatitis B, hepatitis C and cirrhosis as high-risk groups for HCC. Most of guidelines recommended screening intervals was 6 months. The latest guidelines in Europe and the United States recommended ultrasound for screening HCC. The combination of ultrasound and AFP was recommended in the Asian guidelines. Currently, HCC screening guidelines mainly recommended screening strategies based on factors such as risk of HCC, accuracy of screening modality, screening cost, etc.. The key factors such as screening efficacy and safety have not yet been considered comprehensively. Conclusions:There were no independent HCC screening guidelines worldwide. Only some clinical practice HCC guidelines briefly mentioned HCC screening. Currently, the guidelines only recommend screening for high-risk groups of HCC, with a screening interval of 6 months. There are differences in screening modalities recommended by European, American and Asian guidelines for screening HCC. It is suggested that the relevant institutions should formulate the evidence-based HCC screening guidelines by referring to the theoretical framework of other authoritative other cancer screening guidelines.