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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Global utilization of kidney replacement therapy for patients transitioning from chronic kidney disease (CKD) to kidney failure is rising with substantial healthcare and economic impacts. A critical distinction exists between patients who initiate dialysis in a planned versus unplanned manner, as these pathways may lead to different treatment trajectories and resource utilization. Understanding how planned and unplanned dialysis influence kidney replacement therapy patterns—including modality changes, kidney transplantation, and mortality—is essential for optimizing care in this population.
We conducted a population-based observational cohort study of all adult (≥18 years) Ontario, Canada residents with advanced CKD (eGFR <30 mL/min per 1.73m2 and urine albumin-to-creatinine ratio [UACR] ≥265 g/mol) between 2015-2023. A multi-state model was developed to describe transition rates among treatment states including kidney transplantation, peritoneal dialysis, hemodialysis, and death. The state space was augmented to separate patients who had an unplanned (or “crash”) dialysis start from those with a planned start. Parametric hazard models were fit to smooth estimates and extrapolate hazard functions over longer time horizons. Simulations using the fitted multi-state model were performed to obtain time-continuous estimates of treatment state prevalence.
51,737 patients with median (IQR) age 75 (40-93) years, eGFR 24 (11-30) mL/min per 1.73m2, and UACR 32 (4-640) g/mol were included in the cohort. The multi-state model captured significant differences in treatment trajectories between unplanned dialysis and planned dialysis patient subgroups. Patients who initiated dialysis in an unplanned manner experienced approximately 2-fold higher accumulated risk intensity for subsequent mortality, greater short- and long-term mortality rates, lower transplantation rates, and disproportionately higher hemodialysis utilization, compared to those who initiated dialysis in a planned fashion.
This multi-state model captures the significantly different outcomes faced by patients who initiated dialysis in an unplanned manner compared to those who initiated in a planned manner. This model may facilitate economic evaluations towards guiding the effective selection of decision-support tools for the prevention of unplanned dialysis.
