Abstract: FR-OR64
Derivation of a Simple Risk Model for Cardiac Surgery-Associated AKI
Session Information
- Innovative AKI Strategies and Drug Discoveries
October 25, 2024 | Location: Room 7, Convention Center
Abstract Time: 04:30 PM - 04:40 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Durai, Lavanya, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Dias, Julie-Alexia, Harvard T H Chan School of Public Health, Boston, Massachusetts, United States
- Short, Samuel, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Sabe, Ashraf, Brigham and Women's Hospital, Boston, Massachusetts, United States
- Redaelli, Simone, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
- Schaefer, Maximilian S., Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
- Garcia, Daniela, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
- Khabbaz, Kamal, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
- Shaefi, Shahzad, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
- Leaf, David E., Brigham and Women's Hospital, Boston, Massachusetts, United States
Background
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a frequent postoperative complication. Existing models to predict CSA-AKI have key limitations, including reliance on diagnostic codes, use of noncontemporary data, a focus on AKI requiring dialysis, and inclusion of intra/postoperative variables. Further, most studies are single-centered.
Methods
We collected detailed data from 36,658 adults who underwent cardiac surgery at 3 academic medical centers in Boston, MA, between 2008-2022. Data were derived from the Society for Thoracic Surgeons Database, which includes >1,000 perioperative variables, along with electronic medical records. Candidate predictors included demographics, comorbidities, medications, labs, illness severity, and surgical characteristics, each assessed preoperatively. The primary outcome was CSA-AKI, defined as a ≥100% increase in serum creatinine or dialysis initiation within 5 days following surgery. We used multivariable logistic regression with backward elimination.
Results
A total of 1687 patients (4.6%) developed CSA-AKI. The final model included 15 variables (Fig. 1A). A higher CSA-AKI score monotonically predicted a higher risk of CSA-AKI (Fig. 1B). Patients in the highest risk group had a 33.10-fold higher risk of CSA-AKI than those in the lowest risk group (Fig. 1C). The model had significantly better discrimination for CSA-AKI (AUC 0.75) than previously published models tested in the current cohort, the AUCs for which ranged from 0.64 to 0.69 (P<0.001) (Fig. 1D).
Conclusion
A simple 15-variable risk score predicts CSA-AKI more accurately than previously published models.