HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) All Versions of this Article: CJN.00910209v1 4/7/1195    most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Nessim, S. J. Articles by Jassal, S. V. PubMed PubMed Citation Articles by Nessim, S. J. Articles by Jassal, S. V.

Predictors of Peritonitis in Patients on Peritoneal Dialysis: Results of a Large, Prospective Canadian Database

Sharon J. Nessim^*, Joanne M. Bargman, Peter C. Austin, Rosane Nisenbaum^,||, and Sarbjit V. Jassal

^* Department of Medicine, Division of Nephrology, St. Michael's Hospital, Centre for Research in Inner City Health and Applied Health Research Centre, Keenan Research Centre, LiKaShing Knowledge Institute, St. Michael's Hospital, Department of Medicine, Division of Nephrology, Toronto General Hospital–University Health Network, Institute for Clinical Evaluative Sciences, and ^|| Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

Correspondence: Dr. Sharon J. Nessim, 30 Bond Street, 8CC Hemodialysis Unit, Toronto, Ontario, M5B 1W8, Canada. Phone: 416-864-6016; Fax: 416-864-5608; E-mail: nessims{at}smh.toronto.on.ca

Background and objectives: Despite the decreasing incidence of peritonitis among peritoneal dialysis (PD) patients over time, its occurrence is still associated with significant morbidity and mortality. Determining factors that are associated with PD peritonitis may facilitate the identification of patients who are at risk.

Design, setting, participants, & measurements: Using data collected in the multicenter Baxter POET database between 1996 and 2005, the study population included incident Canadian PD patients. Potential predictors of peritonitis were sought using a negative binomial model and an Andersen-Gill model. Study variables included age, gender, race, cause of renal disease, diabetes status, transfer from hemodialysis (HD), previous renal transplant, and continuous ambulatory PD (CAPD) versus automated PD (APD).

Results: Data were available for 4247 incident PD patients, including 1605 patients with a total of 2555 peritonitis episodes. Using the negative binomial regression model, factors that were independently associated with a higher peritonitis rate included age, Black race, and having transferred from HD. There was an interaction between gender and diabetes, with an increased risk for peritonitis among female patients with diabetes. The use of CAPD versus APD did not affect the peritonitis rate. The Andersen-Gill model for recurrent events yielded similar results.

Conclusions: Predictors of PD peritonitis included Black race, transferring from HD to PD, and diabetes among women. In contrast to previous findings, CAPD and APD were similar with regard to peritonitis risk.