Peritoneal Dialysis Associated Peritonitis Rate – Validation of a Simplified Formula

Simplified calculation of PD peritonitis rate

Authors

DOI:

https://doi.org/10.25796/bdd.v4i4.63443

Keywords:

ANZDATA, NZ PD Registry, RDPLF, peritonitis rate computation

Abstract

Peritonitis is the most important therapy-related complication of peritoneal dialysis (PD). Unfortunately, many PD centers around the world do not accurately record peritonitis rate, mainly because they cannot ascertain PD patient time-at-risk from “patient flow” data - that is, calculating PD patient-days from dates when patients start and finish PD. We propose a simplified method of calculating PD peritonitis rate using PD patient time-at-risk from “patient stock” data - - that is, calculating PD patient-days from the number of prevalent PD patients at the center at the start of the year and the corresponding number at the end. We compared gold-standard measurements of annual PD peritonitis rates with simplified ones in the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) / New Zealand (NZ) PD Registry, and Le Registre de Dialyse Péritonéale de Langue Française et hémodialyse à domicile (the RDPLF). A total of 268 centers from 9 countries with 4311 center-years and 110,185 patient-years of follow-up were modelled. Overall agreement was excellent with a concordance correlation coefficient of 0.978 (95% confidence interval [CI] 0.975-0.980) in ANZDATA / NZ PD Registry, and 0.978 (0.977-0.980) in the RDPLF. There was statistically significant lower agreement for smaller centers in the registries at 0.972 (0.966-0.976) and 0.973 (0.970-0.976) respectively, although the performance of the simplified formula remains clinically sound in even these centers. The simplified method of calculating PD peritonitis rate is accurate, and will allow more centers around the world to measure, report, and work on reducing PD peritonitis rates.

References

Marshall MR. A systematic review of peritoneal dialysis-related peritonitis rates over time from national or regional population-based registries and databases. Peritoneal Dialysis International.0(0):0896860821996096.

Sahlawi MA, Wilson G, Stallard B, Manera KE, Tong A, Pisoni RL, et al. Peritoneal dialysis-associated peritonitis outcomes reported in trials and observational studies: A systematic review. Peritoneal Dialysis International. 2020;40(2):132-40.

Manera KE, Johnson DW, Craig JC, Shen JI, Gutman T, Cho Y, et al. Establishing a Core Outcome Set for Peritoneal Dialysis: Report of the SONG-PD (Standardized Outcomes in Nephrology-Peritoneal Dialysis) Consensus Workshop. Am J Kidney Dis. 2020;75(3):404-12.

Manera KE, Tong A, Craig JC, Shen J, Jesudason S, Cho Y, et al. An international Delphi survey helped develop consensus-based core outcome domains for trials in peritoneal dialysis. Kidney Int. 2019;96(3):699-710.

Li PK-T, Szeto CC, Piraino B, de Arteaga J, Fan S, Figueiredo AE, et al. ISPD Peritonitis Recommendations: 2016 Update on Prevention and Treatment. Perit Dial Int. 2016;36(5):481-508.

Szeto C-C, Li PK-T, Johnson DW, Bernardini J, Dong J, Figueiredo AE, et al. ISPD Catheter-Related Infection Recommendations: 2017 Update. Peritoneal Dialysis International. 2017;37(2):141-54.

Gliklich RE, Dreyer NA: Registries for Evaluating Patient Registries: A User’s Guide: AHRQ publication No. 07-EHC001. Rockville, MD. April 2007.

McDonald SP, Russ GR, Kerr PG, Collins JF. ESRD in Australia and New Zealand at the end of the millennium: a report from the ANZDATA registry. Am J Kidney Dis. 2002;40(6):1122-31.

Hayat A, Collins J, Saweirs W. Study of early complications associated with peritoneal dialysis catheters: an analysis of the New Zealand Peritoneal Dialysis Registry data. Int Urol Nephrol. 2021;53(8):1705-11.

Hayat A, Saweirs W. Predictors of technique failure and mortality on peritoneal dialysis: An analysis of New Zealand peritoneal dialysis registry data. Nephrology (Carlton). 2021;26(6):530-40.

Verger C, Fabre E, Veniez G, Padernoz MC. Synthetic 2018 data report of the French Language Peritoneal Dialysis and Home Hemodialysis Registry (RDPLF). Bull Dial Domic. 2019;2(1):1-7 DOI:10.25796/bdd.v2i1.19093.

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases. 1987;40(5):373-83.

Lin LI-K. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45(1):255-68.

Lin LI-K. Assay Validation Using the Concordance Correlation Coefficient. Biometrics. 1992;48(2):599-604.

Lin LI-K. A note on the concordance correlation coefficient. Biometrics. 2000;56(1):324-5.

Krippendorff K. Bivariate Agreement Coefficients for Reliability of Data. Sociological Methodology. 1970;2:139-50.

Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307-10.

Altman DG, Bland JM. Interaction revisited: the difference between two estimates. BMJ. 2003;326(7382):219.

Published

2021-12-15

How to Cite

1.
Marshall M, Waters GP, Verger C. Peritoneal Dialysis Associated Peritonitis Rate – Validation of a Simplified Formula : Simplified calculation of PD peritonitis rate . Bull Dial Domic [Internet]. 2021 Dec. 15 [cited 2024 Dec. 22];4(4):245-57. Available from: https://bdd.rdplf.org/index.php/bdd/article/view/63443