Abstract: FR-PO081
Multistate Modeling Patient Transitions from AKI to CKD or Death Using Electronic Health Records (EHR)
Session Information
- AKI: Epidemiology, Risk Factors, and Prevention - 2
October 25, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Nestor, Jordan Gabriela, Columbia University, New York, New York, United States
- Fang, Yilu, Columbia University, New York, New York, United States
- Weng, Chunhua, Columbia University, New York, New York, United States
Background
Patients with AKI are at high risk for CKD and death. The epidemiology of these transitions is poorly understood. This study aims to characterize patient health trajectories from the initial AKI episode to CKD or all-cause mortality using EHR data from NewYork-Presbyterian/Columbia University.
Methods
This retrospective study included 20,699 patients. Clinical states were identified by clustering patient vectors derived from temporal medical codes and serum creatinine (SCr) time series using natural language processing models. Transition probabilities between clinical states and to outcomes (CKD or death) were estimated using multi-state modeling.
Results
In the AKI cohort, 17% developed CKD and 19% died. We identified 15 clinical states with varying disease burdens. Each state had unique transition probabilities over 5 years (Figure). Risk factors for each outcome were identified within different AKI subpopulations based on clinical state trajectories (Table).
Conclusion
This study enhances our understanding of patient trajectories from an initial AKI episode to CKD diagnosis or death by tracking the progression of medical conditions, interventions, treatments, and SCr levels over time.
Figure: Transition Probabilities Between Clinical States Over a 5-Year Period
Table: Risk Factors for CKD and All-Cause Mortality for Each Initial State Transition
Funding
- Other NIH Support