Objective To analyze the status and impact factors of continuous rehabilitation nursing about stroke patients.Methods 120 medical staff in 6 hospitals and 108 medical staff in 9 community using the multi-stage random sampling method were investigated with questionnaires designed by ourselves.Results Lacking communication and cooperation between hospitals and community medical center,lacking unified and normative regulation and standards were the main influencing factors of the continuous rehabilitation nursing.Conclusions We should establish information interactive platform and perfect the corresponding policies to build continuous rehabilitation nursing model.

Objective To explore the effects of WeChat-based peer education on improving special position compliance in patient after retinal detachment and to provide reference for clinical nursing staff.Methods Totally 82 patients after retinal detachment who were hospitalized in the First Affiliated Hospital of Zhengzhou University from March 2017 to April 2018 were selected by purposive sampling and randomly divided into the control group (n=41) and the intervention group (n=41) according to the random number table.Patients in the control group received conventional health education,while patients in the intervention group received WeChat-based peer education on the basis of conventional health education.The special position compliance and the incidence rate of complications 3 months post surgery were compared between the two groups.Their satisfaction with the WeChat-based peer education was also evaluated.Results The score of special position compliance in the intervention group was (5.23±0.854),higher than that of the control group (P＜0.01),which was (2.11±0.997).The incidence rate of nuchal muscle pain,headache,dizziness and insomnia caused by special positions in the intervention group was lower than that in the control group (P＜ 0.05).The patients' satisfaction with the WeChat-based peer education was 92.68%.Conclusions The WeChat-based peer education improves patients' awareness of diseases and enhance their confidence in recovery,thereby improving their special position compliance and accelerating recovery.

Purpose/Significance To construct a risk prediction model for postoperative massive bleeding in nasopharyngeal carcino-ma after radiotherapy,and to evaluate its predictive performance.Method/Process Inpatients with major bleeding after radiotherapy for nasopharyngeal cancer in the First Affiliated Hospital of Zhengzhou University from 2016 to 2019 are selected as the study objects,and the same number of patients without major bleeding are randomly selected as the control group.The medical record index data of the two groups of patients are collected,and various machine learning algorithms are applied respectively and the optimal algorithm is selected to build the model.Result/Conclusion The model based on support vector machine(SVM)algorithm has a recall rate of 0.94,an F1 val-ue of 0.93,and a precision of 0.93,showing the best performance.It can be used to construct a prediction model for postoperative mas-sive bleeding in nasopharyngeal carcinoma,and provide more accurate personalized prediction for patients,which has good clinical appli-cation prospects.

Objective:To evaluate the relationship between dyslipidemia and uric acid urolithiasis, and explore the risk factors of uric acid urolithiasis.Methods:93 patients with uric acid urolithiasis identified by stone composition analysis were retrospective analyzed from January 2014 to October 2019 were classified as uric acid urolithiasis group.Among them there were 77 men accounting for 82.8%, 16 women accounting for 17.2%, the median age is 64 years old.According to sex, age and other conditions, 321 patients with calcium oxalate urolithiasis in the same period were selected as calcium oxalate stone group. Among them there were 264 men accounting for 82.2%, 57 women accounting for 17.8%, the average age is 64 years old.While 306 non-stone people examined in hospital as control group in the same period who matched with age and gender. Among them there were 252 men accounting for 82.4%, 54 women accounting for 17.6%, the average age is 61 years old. There was no significant difference in age and sex ratio among the three groups. The body mass index (BMI) of uric acid urolithiasis group, calcium oxalate urolithiasis group and control group were significantly different( P<0.01). Serum uric acid, urine pH and blood lipids: triglyceride (TG), cholesterol (TC), high density lipoprotein (HDL-C) and low density lipoprotein (LDL-C) were recorded in the three groups, and the correlation between the above indexes and stone composition was analyzed.The uric acid urolithiasis group was divided into hyperuricemia(HUA) group (n=41) and Non HUA group (n=52) according to serum uric acid, and 66 cases with HUA were selected in the control group. The dyslipidemia and urine pH levels of the above three groups were compared. The multivariate Logistic regression analysis was used to identify the independent risk factors associated with uric acid urolithiasis formation. Results:There were significant differences in TG level, incidence of hypertrigly-ceridemia, low HDL-cholesterolemia, high LDL-cholesterolemia, serum uric acid and urine pH between uric acid urolithiasis group and calcium oxalate urolithiasis group( P<0.05). Significant differences were seen in TG level, HDL-C level, incidence of hypertriglyceridemia and low HDL-cholesterolemia, serum uric acid and urine pH between uric acid urolithiasis group and control group.There was significant difference in urine pH between uric acid urolithiasis with and Non HUA group. Significant difference in the incidence of hypertriglyceridemia and low HDL-cholesterolemia were seen between uric acid urolithiasis with HUA group and HUA group.Multivariate Logistic regression analysis showed that obesity(odds ratio=1.68, P<0.001), hypertriglyceridemia(odds ratio=7.37, P=0.002), low HDL-cholesterolemia(odds ratio=10.46, P=0.001) and low urinary pH(odds ratio=0.10, P<0.001) were independent risk factors for uric acid urolithiasis. Conclusions:Dyslipidemia was more likely associated with uric acid urolithiasis. Obesity, hypertriglyceridemia, low HDL-cholesterolemia and low urinary pH are closely related to the occurrence of uric acid urolithiasis.