Literature DB >> 17699285

Predictive value of dialysate cell counts in peritonitis complicating peritoneal dialysis.

Kai Ming Chow1, Cheuk Chun Szeto, Kitty Kit-Ting Cheung, Chi Bon Leung, Sunny Sze-Ho Wong, Man Ching Law, Yiu Wing Ho, Philip Kam-Tao Li.   

Abstract

Early prediction of outcomes has major potential implications regarding the management of dialysis-related peritonitis. The outcomes of 565 consecutive episodes of peritonitis complicating peritoneal dialysis between August 2001 and July 2005 were evaluated in relation to the dialysate cell counts. Discriminatory power, based on the area under the receiver-operating characteristic (ROC) curves, of the cell counts was assessed. The findings then were validated externally in a cohort of 217 peritonitis episodes from another dialysis unit. During the study period, 565 episodes of peritonitis were included for analysis, 465 of which had treatment success defined as complete resolution of peritonitis without the need for Tenckhoff catheter removal. Of the remaining 100 episodes (treatment failure), 70 required Tenckhoff catheter removal and 30 had peritonitis-related death. The peritoneal dialysate total white blood cell count on day 3 of peritonitis predicted treatment failure independent of standard risk factors, and it had a higher area under the ROC curve than the dialysate white cell count on day 1 (0.80 versus 0.58; P < 0.0001). Using a peritoneal dialysate white count cut point > or = 1090/mm3 on day 3, the sensitivity was 75% and the specificity was 74% for the prediction of treatment failure (defined as catheter loss or peritonitis-related death). In multiple logistic regression analyses, peritoneal dialysate white count > or = 1090/mm3 on day 3 was an independent prognostic marker for treatment failure after adjustment for conventional risk factors (hazard ratio 9.03; 95% confidence interval 4.40 to 18.6; P < 0.0001). Number of years on peritoneal dialysis; diabetes; gram-negative organisms; and Pseudomonas, fungal, or Mycobacterium species were other independent risk factors that were predictive of treatment failure. Findings from an independent validation set of peritonitis (217 episodes after exclusion of Mycobacterium and fungal causes) also favored the peritoneal dialysate white count on day 3, as compared with day 1 and day 2, to predict treatment failure. Area under the ROC curve for the white counts on day 3 was 0.98 (95% confidence interval 0.95 to 0.99) in the validation set. This study demonstrated and cross-validated the superiority of peritoneal dialysate white cell count on day 3 to predict outcomes of dialysis-related peritonitis. These results call attention to the value of validating prognostic factors of peritonitis complicating peritoneal dialysis.

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Year:  2006        PMID: 17699285     DOI: 10.2215/CJN.01010306

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  24 in total

Review 1.  Peritoneal Dialysis-Associated Peritonitis.

Authors:  Cheuk-Chun Szeto; Philip Kam-Tao Li
Journal:  Clin J Am Soc Nephrol       Date:  2019-05-08       Impact factor: 8.237

2.  Clinical characteristics and outcomes of peritoneal dialysis-related peritonitis with different trends of change in effluent white cell count: a longitudinal study.

Authors:  Rong Xu; Yuan Chen; Suping Luo; Ying Xu; Bo Zheng; Yingdong Zheng; Jie Dong
Journal:  Perit Dial Int       Date:  2013-06-03       Impact factor: 1.756

3.  Pseudomonas luteola peritonitis with favorable outcome in continuous peritoneal dialysis.

Authors:  Darlene Gabaldon; Brenda Wiggins; Antonios H Tzamaloukas
Journal:  Int Urol Nephrol       Date:  2013-07-17       Impact factor: 2.370

Review 4.  Peritoneal dialysis-related infections recommendations: 2010 update. What is new?

Authors:  Olga Nikitidou; Vassilios Liakopoulos; Triantafillia Kiparissi; Maria Divani; Konstantinos Leivaditis; Nicholas Dombros
Journal:  Int Urol Nephrol       Date:  2011-07-09       Impact factor: 2.370

5.  Risk factors for drainage-requiring ascites after refractory peritonitis in peritoneal dialysis patients.

Authors:  Cheng-Chia Lee; Kun-Hua Tu; Hsiao-Hui Chen; Ming-Yang Chang; Cheng-Chieh Hung
Journal:  Int Urol Nephrol       Date:  2016-08-05       Impact factor: 2.370

Review 6.  Clinical research in a modern Chinese peritoneal dialysis center.

Authors:  Jie Dong; Ming-hui Zhao
Journal:  Perit Dial Int       Date:  2014-06       Impact factor: 1.756

7.  Risk factors that determine removal of the catheter in bacterial peritonitis in peritoneal dialysis.

Authors:  Rapur Ram; Gudithi Swarnalatha; C Shyam Sundar Rao; G Diwakar Naidu; Sriperumbaduri Sriram; Kaligotla Venkata Dakshinamurty
Journal:  Perit Dial Int       Date:  2014 Mar-Apr       Impact factor: 1.756

8.  Outcome of accidental peritoneal dialysis catheter holes or tip exposure.

Authors:  Douglas M Silverstein; Jennifer E Wilcox
Journal:  Pediatr Nephrol       Date:  2010-02-16       Impact factor: 3.714

9.  Bacteria-derived DNA fragment in peritoneal dialysis effluent as a predictor of relapsing peritonitis.

Authors:  Cheuk-Chun Szeto; Ka-Bik Lai; Bonnie Ching-Ha Kwan; Kai-Ming Chow; Chi-Bon Leung; Man-Ching Law; Vincent Yu; Philip Kam-Tao Li
Journal:  Clin J Am Soc Nephrol       Date:  2013-10-03       Impact factor: 8.237

10.  The negative impact of early peritonitis on continuous ambulatory peritoneal dialysis patients.

Authors:  Yao-Peng Hsieh; Shu-Chuan Wang; Chia-Chu Chang; Yao-Ko Wen; Ping-Fang Chiu; Yu Yang
Journal:  Perit Dial Int       Date:  2014-02-04       Impact factor: 1.756

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