Objective:To explore the trajectory of frailty changes in patients receiving maintenance hemodialysis and analyze its influencing factors.Methods:Maintenance hemodialysis patients at the Blood Purification Center of the Minda Hospital of Hubei Minzu University from January to October 2022 were selected by convenience sampling. The Clinical Frailty Scale (CFS) was used to survey patients at the start of dialysis and one, three, six, and 12 months of dialysis. Latent class growth modeling was employed to identify the potential classes of frailty trajectory changes and analyze the influencing factors of these classes.Results:A total of 255 questionnaires were distributed, with 212 valid responses, yielding an effective response rate of 83.14%. The changes in frailty among the patients receiving maintenance hemodialysis were categorized into three groups: moderate frailty worsening group ( n=64), frailty improvement group ( n=110), and stable pre-frailty group ( n=38). The average probabilities of patients belonging to each latent class were 0.948, 0.938, and 0.950, respectively. Age, gender, body mass index, anemia, continuing to work after illness onset, and comorbidities were identified as influencing factors of frailty trajectory changes in these patients (all P<0.05) . Conclusions:There are three types of frailty trajectory changes in patients receiving maintenance hemodialysis from the start of dialysis to 12 months of regular dialysis. Targeted interventions can be implemented based on the identified influencing factors.

Objective:To investigate the current situation of working pressure of medical staff in a Class Ⅲ Grade A hospital of Haikou city and analyze its influencing factors, in order to provide reliable basis for the pressure management of medical staff.Methods:Using the stratified random sampling method, a total of 300 subjects were selected from medical staff of various departments in Haikou Hospital affiliated to Haikou Affiliated Hospital of Central South University, Xiangya School of Medicine according to the random number table method from December 1 to December 31, 2019. The Working Stressors Scale and general situation questionnaire were used to investigate the medical staff. Multiple linear regression analysis was used to analyze the influencing factors of working pressure of medical staff. A total of 300 questionnaires were sent out and 292 were recovered, with the effective recovery rate of 97.33% (292/300) .Results:The total score of Working Working Stressors Scale for 292 medical staff in a Class Ⅲ Grade A hospital in Haikou city was (2.70±0.25) , which was at a medium pressure level, indicating that the work pressure of medical staff was high. Multiple linear regression analysis results showed that gender, marriage, post and department entered the regression equation ( P<0.05) , which could explain 13.3% of the total variation ( F=8.452, P<0.01) . Conclusions:The work pressure of medical staff in Haikou city is high, and it is affected by factors of gender, marriage, post and department, so it is necessary to carry out targeted stress management and take corresponding intervention measures according to different stressors of medical staff.