Prediction model and influencing factors of capacity management behavior in maintenance hemodialysis patients

To investigate the current status of capacity management behavior in maintenance hemodialysis (MHD) patients and explore related influencing factors.

A total of 115 patients' clinical data were collected, and questionnaire data were collected from patients, including general information, capacity management behavior, self-efficacy, health literacy, etc. The current status of capacity management behavior in MHD patients and the influencing factors of capacity management behavior in MHD patients were analyzed, and a capacity management behavior prediction model was established.

The total score of capacity management behavior in 115 MHD patients was (18.47±2.66) points. The score for blood dialysis related indicators was (12.24±1.95) points, and the score for dietary management was (6.23±1.41) points. There were 46 cases with poor volume management and 69 cases with good management. Univariate analysis showed that there were statistically significant differences in capacity management behavior among patients of different genders, ages, educational backgrounds, work statuses, dialysis ages, and malnutrition risks(P < 0.05). The logistic regression analysis results showed that education, dialysis age, malnutrition risk, self-efficacy, and health literacy were the influencing factors of capacity management behavior in MHD patients (P < 0.05). The construction of a nomogram prediction model showed that the model predicted well.

The capacity management behavior of MHD patients is influenced by multiple factors. Clinical prediction models can be used for early warning screening. Patients with low education, dialysis experience of more than 5 years, risk of malnutrition, low self-efficacy scores, and poor health literacy need to be given more attention, and various forms of targeted intervention measures should be taken to improve capacity management behavior.