Abstract: FR-PO0131
Neural Network-Based Risk Score Prediction of Severe AKI: Clinical Outcomes in a High-Risk Cohort
Session Information
- AKI: Epidemiology and Clinical Trials
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 102 AKI: Clinical, Outcomes, and Trials
Authors
- Fatima, Aiman, The University of Chicago Division of the Biological Sciences, Chicago, Illinois, United States
- Anjorin, Ola, The University of Chicago Division of the Biological Sciences, Chicago, Illinois, United States
- Koyner, Jay L., The University of Chicago Division of the Biological Sciences, Chicago, Illinois, United States
Background
Timely identification of patients at risk of severe acute Kidney Injury (AKI) may allow for clinical interventions and reduce adverse outcomes and the burden of AKI. Artificial intelligence-based risk scores may help identify patients earlier and improve outcomes.
Methods
We identified inpatients at the University of Chicago who were deemed high risk for Stage 2 or higher AKI (severe AKI) based on having an ESTOP (recurrent neural network-based) AKI risk score > 0.091, within the last 8 hours. Demographics, history, AKI rates, mortality, and 90-day outcomes were collected. We recorded the incidence of KDIGO AKI for all patients at 2 and 7 days. We excluded patients who already had stage 2 or higher AKI during their admission as well as those with ESRD and kidney transplants.
Results
We enrolled 95 patients, through day 7 43(54%) patients had severe AKI (stage2/3) while 37(46%) had non-severe AKI (stage 1) and 15(16%) never developed any AKI. In the severe AKI cohort, 30(70%) patients had a maximum of stage 2 AKI while 13(30%) developed stage 3 AKI; 3(7%) of whom received dialysis. Severe AKI developed within the first 48 hours in 31(33%) patients. The baseline serum creatinine (6-month prior median value) was 1.16 for the entire cohort, with no significant difference between those with and without severe AKI. For patients developing severe AKI across 7 days (n=43);12(28%) had serum creatinine(scr) based AKI, 22(51%) had UOP based and 9(21%) had severe AKI by both criteria. Outcomes data in the table shows no association between length of ICU or inpatient stay, 90 days repeat hospitalization across those with and without severe AKI. The inpatient mortality rate was high in those with severe AKI (p=0.01).
Conclusion
Clinical implementation of ESTOP-AKI risk score identifies patients who are at risk of developing severe AKI.
Characteristics of Severe vs Non-severe AKI cohort
| Characteristics | Non-severe AKI(n=37) | Severe AKI (n=43) | p-value |
| Bscr | 1.12 (0.88 -1.3) | 1.06 (0.86-1.36) | 0.70 |
| Enrollment Scr | 1.4 (1.19-1.82) | 1.6 (1.1-2.1) | 0.35 |
| ICU (n) | 28 (76%) | 31 (71%) | 0.72 |
| Total LOS (days) | 9 (5-23) | 12 (7-22) | 0.90 |
| LOS, ICU (days) | 5.5 (3-17.5) | 7 (2-22) | 0.95 |
| Mortality (n) | 5 (13.7%) | 16 (37%) | 0.02 |
| 90 day re-admission (n) | 13 (35%) | 10 (23%) | 0.31 |
Funding
- NIDDK Support