Kidney Week

Abstract: SA-PO759

Retrace-Clustering Creatinine Trajectory and Baseline Features for Predicting ESKD

Session Information

• ANCA-Associated Vasculitis, Anti-GBM Disease, and Other RPGN
  October 26, 2024 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Glomerular Diseases

• 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics

Authors

• Ni Cathain, Dearbhail, The University of Dublin Trinity College, Dublin, Ireland

Dearbhail Ni Cathain

• Nazeer, Jamsheela, The University of Dublin Trinity College, Dublin, Ireland

Jamsheela Nazeer, PhD

• Ng, James, The University of Dublin Trinity College, Dublin, Ireland

James Ng, PhD

• Scott, Jennifer, The University of Dublin Trinity College, Dublin, Ireland

Jennifer Scott, MBChB

• Nic an Riogh, Eithne Muireann, The University of Dublin Trinity College, Dublin, Ireland

Eithne Muireann Nic an Riogh, MBChB

• George, Angel Mary, The University of Dublin Trinity College, Dublin, Ireland

Angel Mary George

• White, Arthur, The University of Dublin Trinity College, Dublin, Ireland

Arthur White, PhD

• Little, Mark Alan, The University of Dublin Trinity College, Dublin, Ireland

Mark Alan Little, MBChB, PhD

Background

Patients with ANCA-associated vasculitis (AAV) may experience end-stage kidney disease (ESKD) and mortality. We aim to investigate the connection between the longitudinal trajectory of creatinine and the occurrence of ESKD and mortality.

Methods

We included patients with a minimum of two creatinine measurements, encompassing the baseline period and the following six months (Figure). Creatinine trajectories were formulated using six months of creatinine readings from AAV patients with kidney involvement. We excluded patients who presented with end-stage kidney disease (ESKD). In instances where a patient had multiple creatinine values within a given month, the average of those values was employed. Percentage delta creatinine values, representing the percentage difference between a creatinine value and its baseline, were then calculated. The K-means algorithm for longitudinal data was employed to cluster the creatinine trajectories of AAV patients. The quality of clustering was evaluated using the Calinski-Harabasz Index. We conducted a time-to-event analysis for ESKD and death, assessing the survival rates of the clusters over a five-year follow-up period through Kaplan-Meier Survival analysis.

Results

The study incorporates 273 patients with >1 creatinine values, amounting to a total of 2022 creatinine readings. We identified three renal trajectory groups: A-Stable (140), B-Recovered (N=100), and C- Declining (N=33). The baseline features varied across clusters, specifically in terms of baseline creatinine (284uM, 390uM and 151uM respectively, p<0.001) and ENT involvement (p=0.001). When considering the composite outcome of ESKD and death, Cluster A exhibited a 3-year incidence rate of 23%, Cluster B at 8%, and Cluster C at 28% (p<0.0069).

Conclusion

Trajectory clustering allows for the identification of patients who may require closer monitoring, or targeted interventions based on their cluster assignment and associated risk profile.