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Abstract: PO0213

Phenotyping Inpatient AKI by Serum Creatinine Trajectory

Session Information

Category: Acute Kidney Injury

  • 101 AKI: Epidemiology, Risk Factors, and Prevention

Authors

  • Bowe, Benjamin Charles, Veterans Health Administration, St. Louis, Missouri, United States
  • Xie, Yan, Veterans Health Administration, St. Louis, Missouri, United States
  • Xian, Hong, Saint Louis University, Saint Louis, Missouri, United States
  • Rigdon, Steve E., Saint Louis University, Saint Louis, Missouri, United States
  • Al-Aly, Ziyad, Veterans Health Administration, St. Louis, Missouri, United States
Background

Clinical guidelines for risk stratification of acute kidney injury (AKI) do not fully consider characteristics of changes in serum creatinine that may be informative for future risk of adverse outcomes. Identification of patient groups that display distinct patterns in trajectory of SC during an AKI may enhance risk stratification.

Methods

Latent trajectory model identified trajectory patterns of SC in a cohort of United States Veterans hospitalized with AKI. Trajectories and outcome profiles were used to establish AKI phenotypes. Risk factors for phenotypes were examined, and phenotype discrimination in short-term outcomes was assessed vis-à-vis KDIGO stages.

Results

In a cohort of 360,560 US Veterans with a hospitalization with an AKI, we identifyied 6 phenotypes representing distinct patterns in trajectory of SC during hospitalization. Compared to a trajectory with mild changes in SC (59.4% of cohort), moderate (23.1%), and more severe changes (8.7%) with moderate recovery were associated with decreasing odds of non-recovery in SC by discharge (OR=0.52 and 0.25 respectively), higher odds of receipt of kidney replacement therapy (KRT) (3.8 and 13.8) and death within 30-days of hospitalization (1.8 and 2.5). Those whose SC continued to rise during hospitalization (3.86%) had the lowest odds of recovery (OR=0.02) and highest odds of mortality (8.0). Phenotype with highly increased SC with incomplete recovery (2.81%), or very dynamic change in the first few days of hospitalization (2.15%), were associated with higher odds of KRT (57.3 and 89.4, respectively) and lower odds of recovery (0.08 and 0.11). A prior history of chronic kidney disease, albuminuria, and prior AKI, as well as major in-hospital events including sepsis, admission to ICU, and mechanical ventilation, were associated with trajectories with worse outcomes. Discrimination in future outcomes during course of hospitalization suggested that as the hospitalization progressed, phenotypes increasingly provided more information on risk of future outcomes (C-statistic: 0.72, recovery; 0.87, KRT; 0.62, death) than KDIGO stages (0.62, recovery; 0.75, KRT; 0.59, death).

Conclusion

Our results suggest that leveraging EHR data to profile changes during the occurrence of AKI in kidney function may enhance risk stratification of AKI patients during the course of the hospitalization.

Funding

  • Veterans Affairs Support