Objective:To investigate the epidemiological characteristics of herpangina (HA) and its correlation with the incidence of hand, foot and mouth disease (HFMD) in children aged ≤6 years in Yinzhou District of Ningbo from 2017 to 2022.Methods:Epidemiological characteristics of HA in children aged ≤6 years were analyzed based on the electronic medical record data and public health management data from 2017 to 2022 collected from the Health Information Platform of Yinzhou. The incidence of HFMD was calculated using the infectious disease reporting data from the public health management data. Autoregressive integrated moving average model and cross-correlation function were used to evaluate the correlation between the incidence of HA and HFMD.Results:From 2017 to 2022, a total of 25 385 cases of HA were detected in children aged ≤6 years in Yinzhou, the male-to-female ratio of the cases was 1.12∶1. The average annual incidence of HA was 4 986.67/100 000, with the highest incidence in 2018 (10 477.09/100 000) and the lowest incidence in 2020 (870.88/100 000). The incidence peak of HA was during June to July. The incidence of HA was higher in age group 1 year (7 950.45/100 000) than in other age groups. The incidences of HA in Yunlong, Jiangshan and Xiaying were higher, with the incidence of 8 764.31/100 000, 8 377.58/100 000 and 7 965.31/100 000, respectively. The correlation coefficients between the incidence of HA and HFMD at lag day 0, 7, 12 and 18 were 0.199, 0.139, 0.090 and 0.086, respectively (all P<0.05). Conclusions:From 2017 to 2022, the incidence of HA was high in children aged ≤6 years in Yinzhou with obvious seasonality and area difference. The incidence of HA was correlated with the incidence of HFMD and the incidence of HFMD had certain lags. The comprehensive prevention and control of HA and HFMD should be further strengthened by prioritizing HA surveillance and implementing integrated surveillance and management of HA and HFMD.

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 understand the current status of gastroscopy in diagnosing gastric lesions in general population, and to recommend the optimal age for the first gastroscopy and intervals for repeated gastroscopy.Methods:The gastroscopy records of residents aged 18-80 years in Yinzhou District of Ningbo, Zhejiang Province, between April 2010 and December 2021 were analyzed retrospectively. The detections of gastric lesions across different years, age and genders were described. Goodness of fit tests were applied to compare the differences in detection rates of different lesions in first-time endoscopy in different age groups and different populations. Generalized additive models were used to fit the trend of age specific gastric lesion detection rate explore the optimal age for gastroscopy. The appropriate gastroscopy intervals were determined according to the progress of the gastric lesions detected in repeated gastroscopy.Results:A total of 237 751 participants with 344 398 gastroscopy records were included in analyses. A total of 5 597 cases of chronic atrophic gastritis (CAG), 9 796 cases of intestinal metaplasia (IM), 165 cases of low-grade intraepithelial neoplasia (LGIN), 52 cases of high-grade intraepithelial neoplasia (HGIN) and 435 cases of gastric cancer were detected by the first gastroscopy. The overall detection rate of gastric lesions increased significantly in age group 45-70 years, and remained stable after 70 years old, with LGIN and HGIN showing notable increases at 50 and 55 years old, respectively. Repeated gastroscopy detected CAG, IM, LGIN, and HGIN at a higher rate compared with the first gastroscopy. Normal/superficial gastritis progressed in 3-5 years, whereas CAG or more severe lesions progressed in 1-6 years.Conclusion:Gastroscopy is recommended for general population aged 45 years and above. Furthermore, gastroscopy can be performed every 3-5 years for individuals with normal endoscopy results and once a year for patients with CAG or more severe gastric lesions.

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.

Objective: To investigate the incidence density of adult sleep disorders (SD) in Yinzhou District, Ningbo City, Zhejiang Province from 2017 to 2023, so as to provide insights into formulating the control measures of SD. Methods: The electronic health records of permanent residents aged 18 years and over in Yinzhou District from 2017 to 2023 were collected through the Yinzhou Regional Health Information Platform. New cases of SD were diagnosed for the first time a year after establishing health records. The incidence density was estimated using Poisson distribution. The temporal, population and regional distribution characteristics of new cases of SD were analyzed using a descriptively epidemiological method. Results: From 2017 to 2023, there were 1 255 129 permanent residents aged 18 years and over in Yinzhou District, with a total observed person-time of 6 292 884 person-years and a median of 5.67 (interquartile range, 3.74) person-years. There were 165 490 new cases of SD, including 67 095 males (40.54%) and 98 385 females (59.46%). The incidence density of SD in Yinzhou District from 2017 to 2023 was 26.30/1 000 person-years, with no significant trend observed (P>0.05). The incidence density of SD was higher in females than in males (29.63/1 000 person-years vs. 22.57/1 000 person-years, P<0.05). The highest incidence density of SD was observed in individuals aged 70 to <80 years (63.30/1 000 person-years), and the lowest was in individuals aged 18 to <30 years (7.24/1 000 person-years). The incidence density of SD in individuals aged 30 years and over was higher than that in individuals aged 18 to <30 years (all P<0.05). The incidence density of SD was 32.03/1 000 person-years in individuals with junior high school education or below, which was higher than individuals with senior high school/technical secondary school education (25.93/1 000 person-years) and college degree and above (18.87/1 000 person-years, all P<0.05). Dongliu Street, Dongjiao Street, and Baihe Street had relatively higher incidence densities of SD, at 45.11/1 000 person-years, 42.87/1 000 person-years and 40.16/1 000 person-years, respectively. Conclusions From 2017 to 2023, there was no significant trend in the incidence density of SD in Yinzhou District. Higher incidence density were observed in females, the elderly, and individuals living in central urban areas.

Objective:To study the quality control management method of magnetic resonance equipment based on multi-constraint optimal programming model,and to improve the utilization efficiency and imaging effect of magnetic resonance imaging(MRI)equipment.Methods:By gridding the current carrying area of the superconducting magnet of magnetic resonance equipment,the total length of the superconducting material was calculated,and the optimal programming model of the magnetic resonance superconducting magnet was established with constraints set.The optimal programming results of the superconducting magnet was obtained by solving the model to achieve quality control of the magnetic resonance equipment.Taking the minimum scanning time of magnetic resonance equipment as the objective function,a refined management model of magnetic resonance equipment was established to realize the time planning for the use of magnetic resonance equipment.Using fuzzy set theory,the six magnetic resonance equipment in clinical use in Lishui Branch of Zhongda Hospital Southeast University from 2022 to 2023 was divided into five grades according to the imaging quality of magnetic resonance equipment,including excellent,good,average,below average and poor.The quality control management effect was evaluated from the uniformity of the superconducting magnet imaging magnetic field,the uniformity of 10 magnetic resonance images,the geometric distortion rate,and the total number of monthly scans.Results:After the implementation of the quality control management method for magnetic resonance equipment based on the multi-constraint optimal programming model,the maximum value of the magnetic field uniformity contour of the tested equipment was reduced from 15 ppm to 5 ppm;the uniformity test results of the 10 collected magnetic resonance images showed that 2 were good and 8 were excellent,all of which met the technical standards of magnetic resonance imaging;the mean value of geometric distortion rate of magnetic resonance imaging was at-0.5%～0,and the corresponding test grade was excellent;the number of monthly scans of the human body by the tested magnetic resonance equipment was higher than that before the quality control management,especially the number of lower limb scans increased from 607 times before the quality control management to 821 times,with an increase of 214 times.Conclusion:The quality control management method for magnetic resonance equipment based on multi-constraint optimal programming model can effectively improve the quality and control management level of magnetic resonance equipment,optimize the maintenance and management process of magnetic resonance equipment,improve equipment operation efficiency,and reduce operating costs.

Objective:To validate the performance of cardiovascular risk prediction models based on the Sweden National Diabetes Register (NDR) and Diabetes Lifetime-perspective prediction (DIAL) model for assessing risks of 5-year and 10-year cardiovascular disease (CVD) among Chinese patients with type 2 diabetes.Methods:Based on the Chinese Electronic Health Records Research in Yinzhou study, 83 503 patients with type 2 diabetes aged 30-75 years without a history of CVD at baseline were included from January 1, 2010 to December 31, 2020. Recalibrated NDR model was used to estimate 5-year risk, while the recalibrated DIAL model was used to predict 5-year and 10-year risks. The competing events adjusted Kaplan-Meier analysis was used to obtain the observed cardiovascular events. Discrimination C statistics evaluated model accuracy, calibration χ2 value, and calibration plots. Results:Through a median follow-up of 7.0 years, 7 326 cardiovascular events, and 2 937 non-vascular deaths were identified among a total of 83 503 subjects. The recalibrated NDR model overestimated 5-year risk by 39.4% in men and 8.6% in women, whereas the overestimation for the recalibrated DIAL model was 14.6% in men and 50.1% in women. The DIAL model had a better discriminative ability ( C-statistic=0.681, 95% CI: 0.672-0.690) than NDR model ( C-statistic=0.667, 95% CI: 0.657-0.677) in 5-year risk prediction for men, and the models had a similar ability for women ( C-statistic=0.699, 95% CI: 0.690-0.708 for NDR and C-statistic=0.698, 95% CI: 0.689-0.706 for DIAL). The prediction accuracy of the DIAL model was improved in the 10-year risk, with the underestimation being 1.6% for men and the overestimation being 12.8% for women. Conclusions:Both recalibrated NDR and DIAL models overestimated 5-year cardiovascular risk in Chinese patients with type 2 diabetes, while the higher overestimation was shown using the DIAL model. However, the improvement was found in predicting 10-year CVD risk using the DIAL model, which suggested the value of lifetime risk prediction and indicated the need for research on the lifetime risk prediction model for cardiovascular risk assessment in Chinese patients with type 2 diabetes.

With the rapid development of Internet technology and the continuous advancement of medical informatization, big data in healthcare has gradually become an important resource to innovate health management and meet the growing health needs of people and the application of big data in healthcare has been one of the indispensable parts of national big data strategy in China. Based on the established healthcare big data platform and the application of big data technology, Yinzhou district has made innovative efforts to explore a new model driven by big data for the prevention and control of communicable and non-communicable diseases and the management of vaccination programs. It is expected that the "Internet plus healthcare" model will strengthen the disease prevention and control and public health management in local area, create a new business form and provide strong support for Healthy China 2030. This article introduces this new model driven by big data in Yinzhou and discusses the preliminary efficiency of this model in public health practice.

Objective To investigate the effect of different concentrations of hypertonic saline solution (HS) on intestine injury in rats at the early stage of severe burn. Methods 104 adult healthy female Sprague-Dawley (SD) rats were randomly divided into five groups: sham group (n = 8), lactated Ringer solution (LR) group (n = 24) and 200, 300, 400 mmol/L HS group (HS200 group, HS300 group, HS400 group, all n = 24). All the rats in LR group and different concentrations of HS groups were scalded for 30% total body surface area (TBSA) with Ⅲ degree, after immediately, the rats were given burn resuscitation therapy by LR or corresponding concentrations of HS through the tail vein. Eight rats were sacrificed on the 2nd, 8th and 24th post-injury hour (PIH), respectively, to collect abdominal aorta blood and intestinal tissues. The rats in sham group were given simulation of burns without resuscitation, which were immediately sacrificed and the specimens were harvested. The serum Na+concentration was determined by automatic biochemical analyzer. Tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) contents in serum were determined by enzyme-linked immunosorbent assay (ELISA). The moisture content of intestine reflected by intestine wet/dry weight (W/D) ratio was determined. The content of malondialdehyde (MDA) and the activity of diamine oxidase (DAO) in intestinal tissue were determined by ultraviolet spectrophotometer. The activation of von Willebrand factor (vWF) was assessed by using immunohistochemistry. Results Compared with sham group, and the contents of TNF-α and IL-1β in blood and W/D ratio and MDA contents in intestine at each time point after injury in LR group and three HS groups were significantly increased, and the activity of intestinal DAO was significantly decreased. The serum Na+concentration was significantly reduced in the LR group as compared with that in the sham group, which was significantly higher in the three HS groups than that in the sham group, with the most obvious change on the 8th PIH. Compared with LR group, the serum Na+concentration and the activity of intestine DAO at each time point after injury in different concentrations of HS groups were significantly increased, and the serum contents of TNF-α, IL-1β and the W/D ratio, MDA contents in intestine were significantly lowered showing a dose dependent. The changes of HS400 group was the most significantly, and the difference on the 8th PIH was statistically significant as compared with LR group [blood Na+(mmol/L): 145.51±0.72 vs. 131.52±0.85, intestinal DAO (U/g): 4.85±0.30 vs. 3.50±0.45, blood TNF-α (ng/L):88.47±4.91 vs. 153.21±13.45, blood IL-1β (ng/L): 85.77±3.42 vs. 140.57±10.46, intestinal W/D ratio: 3.32±0.05 vs. 3.73±0.09, intestinal MDA (nmol/mg): 0.58±0.01 vs. 0.82±0.04, all P < 0.05]. The immunohistochemical results showed that the vWF activity in the LR group and different concentrations of HS groups was significantly reduced as compared with that of the sham group. Compared with LR group, the activity of intestinal vWF at each time point in different concentration of HS groups was increased to some extent with a dose dependent. The positive staining in HS400 group was the deepest, which showed that the activity of intestinal vWF was the strongest after treated by 400 mmol/L HS. Conclusion Compared with LR, HS can attenuate intestinal tissue injury of rats at the early stage of severely burned, and of all, the curative effect of 400 mmol/L HS is the best.