Abstract: SA-PO071
Assessing Ambient Heat Exposure and AKI Using Alternate Case Definitions
Session Information
- AKI: Epidemiology, Risk Factors, Prevention - II
November 04, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Rabin, Benjamin, Emory University School of Medicine, Atlanta, Georgia, United States
- Dsouza, Rohan, Emory University School of Public Health, Atlanta, Georgia, United States
- Weil, Ethel Jennifer, Emory University School of Medicine, Atlanta, Georgia, United States
- Chang, Howard, Emory University School of Public Health, Atlanta, Georgia, United States
- Ebelt, Stefanie, Emory University School of Public Health, Atlanta, Georgia, United States
- Scovronick, Noah, Emory University School of Public Health, Atlanta, Georgia, United States
Background
Ambient heat exposure is an established risk factor for the development of acute kidney injury (AKI). However, prior work using International Classification of Disease (ICD)-coded data has important limitations in evaluating heat-AKI. We hypothesized that Kidney Disease: Improving Global Outcomes (KDIGO)-based AKI definitions would improve the accuracy of heat-AKI effect estimates compared to ICD-coded data by improving AKI case sensitivity.
Methods
We conducted a case-crossover study comparing AKI-related emergency department (ED) visits with same-day maximum temperatures in Atlanta, Georgia during 6 consecutive warm seasons. We created 7 case definitions for AKI using ICD-coded data and KDIGO-derived equations. KDIGO definitions compared an individual’s serum creatinine measurements to surrogate values for baseline renal function.
Results
We analyzed 368,682 total ED visits between 2014 and 2019. Cases of AKI ranged from 5,868 to 64,269 across the 7 definitions. Higher temperatures were associated with AKI-related ED visits in all 7 definitions (Figure 1). When we stratified individuals by the presence of an ICD-coded AKI diagosis, we detected a persistent heat-AKI effect among individuals without a coded AKI diagnosis under the "CKD-EPI 75" (OR 1.06, 95% CI 1.02-1.12) and "CKD-EPI 90" (OR 1.07, 95% CI 1.03–1.11) definitions.
Conclusion
Our results support KDIGO-based definitions as an improved tool to evaluate the heat-AKI relationship. This method may enable reseachers to capture additional AKI cases otherwise missed by code-classified data, for whom a significant heat-AKI effect exists.
Exposure response functions by case definition for the risk of AKI across daily maximum temperature (Odds ratios provided with 95% CI).