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.

Objective:Based on the health ecological model, this paper systematically explores the influencing factors of mild cognitive impairment among the elderly herders in Nanshan pastoral area of Xinjiang, and provides the basis for local medical institutions to formulate prevention and control strategies for mild cognitive impairment among the elderly herders.Methods:A total of 1 145 valid questionnaires were collected, all of them were permanent herdsmen aged over 60 years in Nanshan pastoral area of Xinjiang were selected from June 2022 to February 2023 by stratified cluster random sampling method in a cross-sectional survey. Under the guidance of health ecological model, the research variables were included from five dimensions: physiology, psychology, behavioral lifestyle, social network and medical and health environment, and questionnaires were conducted. SPSS 23.0 was used for chi-square test and binary Logistic regression to analyze the influencing factors of mild cognitive impairment in elderly herders.Results:There were 564 males and 581 females with age of (70.84 ± 5.69) years old in the study. The prevalence rate of mild cognitive impairment among elderly herdsmen in Nanshan pastoral area of Xinjiang was 36.1%(413/1 145). Binary Logistic regression analysis showed that: personal monthly income (1 000-2 999 yuan)( OR = 0.583, 95% CI 0.366 - 0.926, P<0.05), education level (junior high school and above)( OR = 0.479, 95% CI 0.315 - 0.728, P<0.01) were the protective factors for mild cognitive impairment among the elderly herdsmen in Nanshan pastoral area. Hypertension ( OR = 1.842, 95% CI 1.256 - 2.702, P<0.01), dyslipidemia ( OR = 1.449, 95% CI 1.069 - 1.964, P<0.05) and chronic pain ( OR = 1.549, 95% CI 1.082 - 2.216, P<0.05) were the risk factors of mild cognitive impairment in elderly herders in Nanshan pastoral area. Conclusions:The prevalence rate of mild cognitive impairment among elderly herders in Nanshan pastoral area of Xinjiang is high, so it is necessary to carry out mild cognitive impairment screening as soon as possible, especially focusing on people suffering from hypertension, dyslipidemia and chronic pain, and making intervention plans to delay the occurrence and development of mild cognitive impairment and improve the quality of life of elderly herders.

Objective:To assess the safety of sitagliptin added to metformin on cardiovascular adverse events in real world patients with type 2 diabetes mellitus(T2DM).Methods:Real world data from Yinzhou Regional Health Care Database were used to select T2DM patients with diagnosis and treatment records in the platform from January 1,2017 to December 31,2022.According to drug prescription records,the patients were divided into metformin plus sitagliptin group(combination group)and metformin monotherapy group(monotherapy group).A series of retrospective cohorts were constructed according to the index date.Finally,full retrospective cohorts were constructed according to propensity score model,including baseline covariates that might be related to outcomes,to match the subjects in the combination group and monotherapy group for the purpose of increasing the comparability of baseline characteristics.The participants were followed up from the index date until the first occurrence of the following events:Diagnosis of outcomes,death,or the end of the study period(December 31,2022).Cox proportional risk model was used to estimate the hazard ratio(HR)and 95％confidence interval(CI)of sitagliptin added to metformin on 3-point major adverse cardiovascular events(3P-MACE)combination outcome and secondary cardiovascular outcomes.Results:Before propensity score matching,the proportion of the pa-tients in combination group using insulin,α glucosidase inhibitors,sodium-glucose transporter 2 inhibi-tors(SGLT-2I)and glienides at baseline was higher than that in monotherapy group,and the baseline fasting blood glucose(FBG)and hemoglobin A1c(HbA1c)levels in combination group were higher than those in monotherapy group.After propensity score matching,5 416 subjects were included in the combination group and the monotherapy group,and baseline characteristics were effectively balanced be-tween the groups.The incidence densities of 3P-MACE were 6.41/100 person years and 6.35/100 per-son years,respectively.Sitagliptin added to metformin did not increase or decrease the risk of 3P-MACE compared with the metformin monotherapy(HR=1.00,95％CI:0.91-1.10).In secondary outcomes analysis,the incidence of cardiovascular death was lower in the combination group than in the monothera-py group(HR=0.59,95％CI:0.41-0.85),and no association was found between sitagliptin and the risk of myocardial infarction and stroke(HR=1.12,95％CI:0.89-1.41;HR=0.99,95％CI:0.91-1.12).Conclusion:In T2DM patients in Yinzhou district of Ningbo,compared with metformin alone,sitagliptin added to metformin may reduce the risk of cardiovascular death,and do not increase the inci-dence of overall cardiovascular events.The results of this study can provide real-world evidence for post-marketing cardiovascular safety evaluation of sitagliptin.

Objective:To establish a risk model of placenta accreta spectrum(PAS) based on the clinical risk factors and ultrasound signs of patients with placenta accreta, and identify severe placenta accreta prenatal.Methods:A retrospective analysis was performed on 121 PAS patients admitted to Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University from January 2018 to June 2022 who were clinically classified or pathologically diagnosed during delivery. The two groups were divided into light and severe groups according to the implantation type. The clinical risk factors and ultrasound signs between the two groups were compared. A risk model of PAS was established based on the clinical risk factors and ultrasound signs to predict the perinatal complications.Results:A total of 130 cases of PAS were clinically diagnosed or pathologically diagnosed with placenta, 9 cases with incomplete clinical data or irregular ultrasound images were excluded, and the remaining 121 cases were included in the study. Among the 121 patients, 64 cases were placental accreta, 39 cases were placental increta, and 18 cases were placenta percreta. The placental accreta was defined as mild group, and the combination of placental increta and placenta percreta were referred to as severe group. There were no significant differences in placenta previa, and the number of uterine cavity operations (all P>0.05). There were significant differences in the number of cesarean section, myometrium thinning, placental lacunae, abnormal vascularization at the utero-bladder junction, bridging vessels at the utero-bladder junction, placental protuberance and cervical involvement (all P<0.05). Binary logistic regression analysis showed that placental lacunae, abnormal vasculization of the utero-bladder interface and the number of cesarean sections were independent risk factors for severe PAS. Based on this, a risk model was established and the ROC curve of each independent risk factor and risk model was plotted respectively. The AUC of the risk model was 0.826, which had better diagnostic efficacy than other independent risk factors. Conclusions:In the prenatal ultrasound classification diagnosis of high-risk patients with PAS, the placental lacunae, abnormal vascularization of utero-bladder interface and the number of cesarean section are combined to establish the risk model of PAS, which has a good diagnostic efficacy for severe placenta accreta.

Objective:To explore the the predictive value of ultrasound signs of the involvement of the cervix in the clinical grade diagnosis of placenta accreta spectrum(PAS) with placenta previa and adverse pregnancy outcomes.Methods:A retrospective analysis was performed on PAS patients with placenta previa diagnosed during delivery or by cesarean section in Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University from January 2018 to March 2021. According to the signs of cervical involvement on prenatal ultrasound, the patients were divided into cervical involvement group and cervical non-involvement group. Logistic analysis was performed on clinical data between the two groups. The clinical data, hysterectomy rate, intraoperative blood loss and clinical diagnosis were compared between the two groups.Results:There were 1 455 patients with PAS diagnosed by clinical diagnosis or placental pathology, of which 170 were with placenta previa, 24 with incomplete clinical data or non-standard ultrasound images, and the remaining 146 patients were included. In the cervical involvement group, all of 6 cases had placenta percreta. Of the 140 cases in the unaffected cervical group, 89 cases (63.6%) had placental accreta, 48 cases (34.3%) had placental increta, and 3 cases (2.1%) had placenta percreta. There were no significant differences of the age and uterine operation history between the two groups. There was significant difference in the number of cesarean sections between the two groups ( P<0.05). There were significant differences in intraoperative blood loss, hysterectomy rate and placenta accreta grade diagnosis between the two groups(χ 2/ Z=4.203, 11.165, 95.248, all P<0.05). Conclusions:The ultrasonographic signs of cervical involvement have a good predictive value for the pregnancy outcome of PAS.

Objectives? To explore the effects of applying growth mentor program in the training of new nurses. Methods? By convenient sampling, the newly recruited nurses who signed official employment contract with the First Affiliated Hospital of Xi'an Jiaotong University were selected as subject. A total of 756 nurses who enrolled from 2008 to 2012 were put into the control group and 812 nurses enrolled from 2013 to 2017 were in the observation group. The control group received routine training while the observation group received the training of the growth mentor program. The two groups was compared in the resignation rate, annual assessment scores, and patients' satisfaction. Results? The differences in resignation rate between the observation group (0.37%) and the control group (1.06%) were statistical significant (P＜0.01). The annual assessment scores of the observation group (88.63±2.17) and patients' satisfaction (96.78±1.76) were all higher than the control group with statistical significance (P＜ 0.01). Conclusions? The establishment and implementation of the new nurses' growth mentor program can significantly reduce the nurses' resignation rate, improve the nurses' professional skills and patients' satisfaction, therefore the program should be widely applied in new nurses' training in hospitals.

Objective To analysis the change of hip joint in healthy infants by ultrasound,and establish the normal reference value of the developmental dysplasia of the hip(DDH). Methods A total of 8 000 healthy infants from 0 to 24 weeks were collected from the Multi-center study of 10 children′s medical centers. Among them,3 855 infants(2 065 females and 1 790 males) with complete data and follow-up were included in this study. All subjects were divided into 6 groups ( ＜4,4～7,8～11,12～15,16～19 and≥20 weeks group). α angle,femoral head length and width,femoral head coverage ratio by acetabulum ( FHC) were measured in the coronal view on the neutral position;distance from pubis to femoral head ( P-H) and distance from ischium to femoral head ( I-H ) were measured in the transverse view on neutral position;distance from femoral head topubis ( H-P) was measured in the posterolateraltransverse view on the flexion position. The results of each group changes with age were analysised. Results ① The α angle of healthy infants from 0 to 20 weeks were increased with age,the difference among the groups were statistically significant( P ＜0.05),but there was no significant difference between 16～19 and ≥20 weeks group( P ＞0.05). ②The femoral head length and width of all age groups were increased with age,the difference among all the groups was statistically significant( all P ＜0.05). ③ FHC from 0 to 20 weeks were increased with age,the difference among the groups were statistically significant( P ＜0.05) except between 16～19 and ≥20 weeks group( P ＞0.05). ④ The P-H and I-H in all age groups showed no statistically significant ( all P＞0.05). ⑤The H-P of all age groups were increased with age,the difference between the groups were statistically significant(all P ＜0.05).Conclusions The development of hip joints have the certain regular developmental pattern in healthy infants less than 5 months of birth and are relatively constant after birth more than 5 months. The ultrasound normal reference value of the hip joints can be used for the early diagnosis of the DDH.

Objective To investigate the related prognostic factors of stage Ⅳ gastric cancer.Methods The clinical data of 248 patients with stage Ⅳ gastric cancer and intact follow up data in the Tumor Prevention and Treatment Center of Sun Yat-Sen University from 2000 to 2010 were retrospectively summarized.The twelve clinicopathological parameters served as the observation indicators,including age,sex,body mass reduction,H b,CEA,CA19-9,Borrmann type,tumor location,tumor size,pathological pattern,operative mode,metastatic sites and therapeutic model.The survival curve was drawn by using the Kaplan-Meier method.The median survival time was calculated.The univariate analysis was conducted with Log-rank test.The prognosis multivariate analysis was conducted by the Cox's proportional hazards regression analysis.Results MST in the patients of whole group was 254 d.The univariate analysis showed that sex,Borrmann type and therapeutic mode were the related factors afecting gastric cancer prognosis,while the Cox regression model revealed that above 3 indicators were also independent factors affecting the prognosis of the patients with stage Ⅳ gastric cancer in this group(P＜0.05).Conclusion The treatment mode is an important independent factor affecting the survival of stage Ⅳ gastric cancer,the translational medicine model of palliative chemotherapy combined with palliative operation conduces to improve the prognosis in the patients with stage Ⅳ gastric cancer.