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.

Peritonitis is the most important therapy-related complication of peritoneal dialysis (PD). Monthly or quarterly PD peritonitis rate statistics are used to identify special cause variation within or between individual PD centres, to highlight any need for quality improvement. Unfortunately, many PD centres do not accurately “patient flow” (i.e., when patients start and finish on PD), and therefore cannot measure PD peritonitis rate. In this study, we validate an estimating formula for month-on-month annualised PD peritonitis rate, that calculates time-at-risk from “patient stock” (i.e., the number of prevalent patients on PD at the beginning and end of the month). We compared centers’ estimated peritonitis rates with gold-standard measurements in the Australia and New Zealand Dialysis and Transplant Registry / New Zealand PD Registry, and Le Registre de Dialyse Péritonéale de Langue Française et hémodialyse à domicile. A total of 268 centers from 9 countries with 1,020,260 patient-months of follow-up and 19,669 episodes of peritonitis were modeled. Overall agreement was excellent between estimates and gold-standard measurements with a concordance correlation coefficient (CCC) of 0.998 (95% confidence interval [CI] 0.998-0.998) in both registries. There was statistically significant lower agreement for smaller centers, although the CCC was still greater than 0.995. There were no instances of clinically significant misclassification of centers as being compliant or non-compliant with PD peritonitis standards with the use of the estimating formula. The simplified method of calculating the PD peritonitis rate is accurate and will allow more centers around the world to measure, report, and work on reducing PD peritonitis rates.

Recently, we validated a simple method for estimating peritoneal dialysis (PD) peritonitis rate. Despite good agreement between estimates and gold-standard measurements in two large dialysis registries, the International Society of Peritoneal Dialysis (ISPD) was hesitant to recommend adoption of the estimating equation. Their perception is that inaccuracies, as small as they are, might still be detrimental to clinical decision-making. In this study, we apply new analyses to the original validation data sets. We quantify agreement using standards from the International Organization for Standardization (ISO). We also identify a subset of centres with poorest performance of the estimating equation and qualitatively assess the potential for compromised clinical decision-making associated with its use. Inter-assay % coefficient of variation between estimates and measurements was 4.2% in the Australia and New Zealand Dialysis and Transplant Registry and 4.6% in Le Registre de Dialyse Péritonéale de Langue Française, easily meeting ISO requirements. Mandel’s h values and Grubb’s tests confirmed more outlying estimates compared to the measurements, while Mandel’s k values and Cochran’s C tests showed that identical precision by the two methods. Misclassification of centres as being above versus below the ISPD standard of 0.4 episodes/patient-year occurred only with rates close to the threshold, affecting approximately 3% of patient-years. In the 26 (out of 268) centres with poorest performance of the estimating equation, examination of the time series of their annual PD peritonitis rate estimates/measurements showed that using estimates would not detrimental to clinical decision-making. In conclusion, the estimating equation is sufficiently accurate for routine clinical use.