The geriatrics department of Zhongnan Hospital covers all subspecialties of internal medicine with six separated wards, so it is difficult to manage and teach the students who participate in standardized training for resident physicians. In the residents' standardized training of geriatrics department, the interactive support platform named micro-teaching assistant was applied to carry out teaching activities such as classroom check-in, classroom testing and classroom discussion of teaching rounds and small lectures. It not only effectively manages the teaching order, but also improves students' enthusiasm and autonomy by encouraging them to participate in classroom interaction actively. The case analysis quiz and interactive discussion have a good effect on consolidating and deepening the students' professional knowledge, and improving the ability of clinical analysis and problem solving. The attendance rates, class discussion and test scores were recorded in a real and objective way, so that teachers can observe the whole process of students' learning and then make a formative assessment. At the same time, teachers are urged to adjust the teaching contents and progress in time, so as to achieve the goal of promoting "teaching" and "learning" mutually.

Objective:To explore the construction of a Logistic prediction model and countermeasures for type 2 diabetic nephropathy based on clinical data.Methods:The patients with type 2 diabetic nephropathy admitted to Shijiazhuang Second Hospital from September 2019 to September 2021 (study group) were selected and the patients were selected according to a 1∶1 ratio using individual matching (control group), each group with 200 patients. Single and multiple factors analysis were used to analyze the factors influencing type 2 diabetic nephropathy, and Logistic regression equation models were developed to verify their predictive value.Results:Logistic regression equation model showed that the course of type 2 diabetes, glycosylated hemoglobin (HbA 1c), fasting plasma glucose (FPG), homocysteine (Hcy), urinary microalbumin, and serum creatinine (Scr) were high risk factors for type 2 diabetic nephropathy ( P<0.05). The results of Logistic regression model evaluation showed that the model was established with statistical significance, and the coefficients of the regression equations had statistically significant differences. The Hosmer-Lemeshow goodness-of-fit test showed that the model fitting effect was good. Logistic regression model was used to statistically analyzed the data set, and the receiver operating characteristic (ROC) curve of type 2 diabetic nephropathy was drawn, the area under the curve was 0.949(95% CI 0.922 - 0.968), the prediction sensitivity was 81.50%, the specificity was 95.50%, the calibration curve showed that the predicted results was in good agreement with the observed results. Conclusions:The independent predictors of type 2 diabetic nephropathy involve HbA 1c, FPG, Hcy, urinary microalbumin. The Logistic prediction model based on these predictors has reliable predictive value and can help guide clinical diagnosis and treatment.

Objective:To investigate the clinical efficacy and safety of amisulpride in the treatment of schizophrenia.Methods:Ninety patients with schizophrenia admitted to Quzhou Third Hospital from August 2020 to March 2022 were included in this study. They were randomly divided into an observation group and a control group ( n = 45/group). The control group was treated with olanzapine, and the observation group was treated with amisulpride. All patients were treated for 8 consecutive weeks. Total response rate, Positive and Negative Syndrome Scale score, Clinical Global Impression Scale-Severity of Illness score, glucose and lipid metabolism indicators, Treatment Emergent Symptom Scale score, and adverse reactions were compared between the two groups. Results:Total response rate was 88.89% (40/45) in the control group and 93.33% (42/45) in the observation group. There was no significant difference in total response rate between the two groups ( χ2 = 0.14, P > 0.05). After treatment, the PANSS score [(52.14 ± 3.99) points] and CGI-S score [(3.05 ± 0.86) points] in the observation group were significantly lower than (56.38 ± 4.05) points and (4.34 ± 0.92) points in the control group ( t = 5.00, 6.87, both P < 0.001). The levels of fasting plasma glucose [(5.25 ± 0.33) mmol/L], total cholesterol [(4.08 ± 0.67) mmol/L], triglyceride [(1.29 ± 0.35) mmol/L], and low density lipoprotein-cholesterol [(2.60 ± 0.31) mmol/L] in the observation group were significantly lower compared with the control group [(6.02 ± 0.51) mmol/L, (4.71 ± 0.59) mmol/L, (1.61 ± 0.26) mmol/L, (2.91 ± 0.34) mmol/L, t = 8.50, 3.61, 4.92, 4.52, all P < 0.001]. High density lipoprotein-cholesterol level in the observation group was significantly higher than that in the control group [(1.57 ± 0.36) mmol/L vs. (1.18 ± 0.42) mmol/L t = -4.73, P < 0.001]. Treatment Emergent Symptom Scale score in the observation group was significantly lower than that in the control group [(2.39 ± 0.58) points vs. (2.87 ± 0.62) points, t = 3.79, P < 0.05]. The incidences of drowsiness [6.67% (3/45)], constipation [8.89% (4/45)], and weight gain [2.22% (1/45)] in the observation group were significantly lower than those in the control group [73.33% (33/45), 28.89% (13/45), 17.78% (8/45), χ2 = 4.14, 4.64, 4.44, P < 0.05]. Conclusion:The efficacy of sulfapride in the treatment of schizophrenia is equivalent to that of olanzapine. Sulfapride is better than olanzapine in improving symptoms and reducing disease severity and has better safety.

Inflammatory immune response runs through the course of ischemic stroke. Different subgroups of CD4 + T cells play a complex and important role in the course of ischemic stroke. Among them, the balance of pro-inflammatory effect of T helper cell 17 (Th17) and anti-inflammatory effect of regulatory T cells (Treg) is closely associated with the outcome of stroke. This article reviews the role of Th17/Treg balance in ischemic stroke, in order to deepen the understanding of the mechanism of immune inflammation after ischemic stroke and explore possible therapeutic targets in the course of ischemic stroke.