Background: Peritoneal dialysis (PD) complications are known to be substantial during treatment. Complications may lead to PD failure. One way to reduce complications is to identify patients at risk early. Objective: The study sought to describe complications and investigate the independent associations among the number of complications and age, distance, comorbidity, level of activity in daily living, and PD self-management. Design, participants and setting: A cross-sectional descriptive study was conducted in 364 patients recruited from June to December 2010 who had undergone PD for at least one year. Methods: Data were collected through self-reported questionnaires and reviewing medical records. Multiple regression analysis was used to identify the independent associations among a number of complications and independent variables. Results: A high prevalence of complications was observed in each of three categories: PD inadequacy - electrolyte imbalance (90.7%); PD-related complications - dyslipidaemia (63.8%); and end-stage renal disease-related complications - mineral and bone disorder (90.7%), anaemia (89.3%), and malnutrition (81%). In multiple regression analysis, comorbidity, PD self-management, level of activity in daily living, and age were independently associated with the number of complications (R2 =.231, p<.001) (F(4,358) = 26.816, p<.001). Comorbidity was the strongest factor in predicting complications. Conclusion: There was a high prevalence of PD complications occurring in one year period before recruiting to the study in this sample. Patients with higher comorbidity, lower self-management, lower level of activity in daily living, and younger age were more likely to have higher a number of complications. These factors should be specified for PD suitability. Promoting self-management will help them to undertake PD safely.
|Original language||English (US)|
|Number of pages||8|
|Journal||Renal Society of Australasia Journal|
|State||Published - Jul 2013|
- Peritoneal dialysis
ASJC Scopus subject areas