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.

Clinical Advanced Analytics Global Medical Office Fresenius Medical Care Waltham USA

Data Science Division EMEA APAC LATAM Regions Clinical Advanced Analytics Global Medical Office Fresenius Medical Care Italia Spa Crema Italy

Department of Medicine and Surgery University of Milano Bicocca Milan Italy

FMC Dialysis Services Slovakia Bratislava Slovakia

Global Medical Office Clinical Affairs CoE Clinical and Therapeutic Governance Fresenius Medical Care Italia Spa Crema Italy

Institute of Social Health at Palacký University Olomouc Olomouc Czech Republic

Marketing Department Fresenius Medical Care Italia Spa Crema Italy

Medical Faculty University of PJ Safarik Kosice Slovakia

Nephrology and Dialysis Unit ASST Monza San Gerardo Hospital Monza Italy

President of Lombardy Section of the Italian Society of Nephrology Medical Director Struttura Complessa di Nefrologia ASST Nord Milano Ospedale Bassini via Gorky 50 20092 Cinisello Balsamo MI Italy

Santa Barbara Smart Health GDTI Fresenius Medical Care Valencia Spain

Struttura Complessa Nefrologia e Dialisi ASST Nord Milano Milan Italy

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