The prognostic reasoning system for chronic kidney disease progression (PROGRES-CKD) may help improve waiting list management for outpatient nephrology services in a second-level public hospital in Italy.

Abstract

Background: The management of patients with non-dialysis dependent chronic kidney disease (NDD-CKD) is challenging due to coexisting diseases, competing risks and uncertainties around optimal transition planning. Such clinical challenges are further exacerbated by physician shortage, coupled with rising service demands, which may hinder timely medical access due to long waiting times. Accurate progression risk assessment may help optimize resource allocation and adapting care based on individual patients' needs. This study validated the Prognostic Reasoning System for Chronic Kidney Disease Progression (PROGRES-CKD) in an Italian public hospital and compared its potential impact on waiting list optimization against physician-based protocols.

Methods: First we first validated PROGRES-CKD by assessing its accuracy in predicting kidney replacement therapy (KRT) initiation within 6 months and 24 months in a historical cohort of patients treated at the San Gerardo Hospital (Italy) between 01-01-2015 and 31-12-2019. In a second study we compared PROGRES-CKD to attending nephrologists' prognostic ratings and simulated their potential impact on a waiting list management protocol.

Results: We included 2005 patients who underwent 11,757 outpatient nephrology visits in 4 years. Most visits occurred for NDD-CKD stage 4 patients; the incidence of KRT onset was 10.8 and 9.32/100 patient-years at the 6 and 24-month prediction horizon cohorts, respectively. PROGRES-CKD demonstrated high accuracy in predicting KRT initiation at 6 and 24 months (AUROC = 0.88 and AUROC = 0.85, respectively). Nephrologists' prognostic performance was highly operator-dependent, albeit always significantly lower than PROGRES-CKD. In the simulation exercise, allocation based on PROGRES-CKD resulted in more follow-up visits for patients progressing to end-stage kidney disease (ESKD) and fewer visits for non-progressing patients, compared to allocation determined by nephrologists' prognosis.

Conclusions: PROGRES-CKD showed high accuracy in a real-world application. Waiting list simulation suggests that PROGRES-CKD may enable more efficient allocation of resources.