Acute Interstitial Nephritis (AIN) Risk Calculator
Identifies the likelihood of acute interstitial nephritis in at-risk patients.
Should only be used for patients in whom a kidney biopsy is being considered.
Result:
Differentiating acute interstitial nephritis (AIN) from other causes of acute kidney injury (AKI) is challenging as none of the currently available non-invasive tests has good accuracy for AIN diagnosis. However, AIN is one of the few causes of AKI with diagnosis-specific management including discontinuation of culprit drug and administration of corticosteroids. While delay in AIN diagnosis and management can lead to permanent kidney damage, an incorrect diagnosis might lead to withdrawal of life saving medications and administration of therapies with side effects.
Using data from patients with biopsy-confirmed AIN from three academic centers, Yale (two phases 2015-18, 2020-23), Indiana university, and Johns Hopkins University, we built a model for AIN diagnosis using a combination of commonly available information in the electronic health record. This model showed an AUC of 0.73 to 0.74 in external validation cohorts with a very high negative predictive value (>90%).
Dennis G. Moledina, MD, PhD, FASN, is an associate professor in the department of internal medicine (section of nephrology) at the Yale School of Medicine. He is a board-certified physician-scientist in internal medicine with a sub-specialization in nephrology. Dr. Moledina is an innovative researcher focused on developing diagnostic tests and tools for various subtypes of acute kidney injury, particularly in improving non-invasive diagnosis of acute interstitial nephritis.
He is an investigator in NIH-funded multicenter consortia including Kidney Precision Medicine Program (KPMP) and Care of Outpatients with Acute Kidney Injury (COPE-AKI). He directs the Yale Kidney BioBank which is a biorepository that has collected samples from over 1200 participants with kidney biopsy confirmed diagnoses.