Objective To explore the potential categories and influencing factors of chronic comorbidity treatment burden in maintenance hemodialysis (MHD) patients. Methods Convenience sampling method was used to select MHD patients between April and May 2023 at Northern Jiangsu People’s Hospital and Jiangdu People’s Hospital as the research subjects. The general information questionnaire, Chronic Disease Comorbidity Treatment Burden Scale, and Health Literacy Scale for Chronic Disease Patients were used for the questionnaire survey. The latent class analysis was used to explore the classification of chronic comorbidity treatment burden in MHD patients, and the multi-class logistic regression analysis was used to explore the influencing factors of comorbidity treatment burden. Results A total of 450 survey questionnaires were distributed, and 406 valid questionnaires were collected, with an effective response rate of 90.22%. According to the latent class analysis results, the comorbidity treatment burden of MHD patients was divided into three potential categories. Among them, there were 26 cases in the low-burden group, 194 cases in the medium-burden group, and 186 cases in the high-burden group. The results of the ordered multi-class logistic regression analysis showed that patient age, educational level, dialysis age, number of comorbidities, and level of economic support were potential factors affecting the comorbidity treatment burden in MHD patients (P<0.05). Conclusions The comorbidity treatment burden of MHD patients can be divided into three potential categories. The age, educational level, dialysis age, number of comorbidities, and level of economic support of patients are potential factors affecting the comorbidity treatment burden in MHD patients.
Patients with type 2 diabetes mellitus often face significant treatment burden, which substantially impacts their quality of life and health outcomes. Reducing treatment burden represents a critical component for improving patient prognosis and enhancing treatment adherence. Based on the cumulative complexity model, this article systematically examines the conceptual connotation and multidimensional characteristics of treatment burden in type 2 diabetes mellitus patients, explores the theoretical extension and application value of cumulative complexity model in the type 2 diabetes mellitus field, elucidates its specific applications and recent advances in treatment burden research, evaluates the limitations of existing assessment tools while proposing a multidimensional assessment framework, and ultimately develops cumulative complexity model based intervention strategies. The findings provide theoretical references for optimizing patient-centered diabetes management approaches and offer novel perspectives for treatment burden intervention.