Peritonitis is the bugbear in PD treatment, as its most important therapy-related complication. Although it accounts for just about 5% of all deaths on PD, the fear of it dissuades many patients from getting on this potentially more patient-friendly form of dialysis.
Given the critical nature of this event, monitoring PD peritonitis rates has been recommended as the key metric to determine the quality of PD care at any given centre.
However – and this may come as a surprise to many – very few centres actually calculate and report peritonitis rates. In a recent systematic review, it was determined that only a minority of health jurisdictions capture PD peritonitis rates in a systematic way. One of the reasons for this is that the formula for calculating this metric (computed as the number of episodes as a function of cumulative time-at-risk) is cumbersome and not well understood.

The major problem is thought to be the inability to accurately access data on “patient flow” – that is, the date when patients start and finish PD.
Using data from two large Registries (Australia and New Zealand Dialysis and Transplant Registry [ANZDATA] / New Zealand [NZ] PD Registry and the Registre de Dialyse Peritoneale de Langue Francaise et hemodialyse domicile [RDPLF]), Mark Marshall and colleagues have now developed a new simplified formula that is easier to use and does not depend on accurate recording of these dates.

They found high degrees of concordance between the peritonitis rates using the gold-standard and the new simplified formula, with the concordance correlation coefficient of 0.978 (95% CI 0.975-0.980) and average bias (95% limits of agreement as defined by Bland and Altman) of 0.002 (-0.138-0.142) in ANZDATA / NZ PD Registry and 0.978 (0.977-0.980) and 0.004 (-0.111-0.119) in the RDPLF.
The formula, however, is based on a key assumption that in any given program, patients start and finish PD at a uniform rate throughout the year (that is, at random).
The authors suggest that this estimation is good enough for almost every type of PD centre, although the accuracy decreases as the number of patients in a program go down. The accuracy is really poor in very small centres with 5 or fewer patients. In their analysis, the very small centres in both registries generally had 3-4 fold more PD peritonitis than average.
In addition to the above, the authors recommend sticking to the gold-standard formula if there is a strong and unbalanced pattern to starting and discontinuation of PD at a centre (e.g. when a centre is rapidly losing patients or gaining them over the year in a non-linear manner); or if the PD peritonitis rate that is close to the clinical threshold of 0.5 PD peritonitis episodes per patient-year. Finally, the authors also caution that this formula has not been tested over a shorter time period (e.g. monthly PD peritonitis rates).