The diagnosis of acute interstitial nephritis caused by infection versus antibiotic-induced interstitial nephritis: a narrative review

Acute interstitial nephritis (AIN) is a significant contributor to acute kidney injury and can be attributed to a variety of factors, including but not limited to allergens or drugs, infections, autoimmune or systemic diseases, and idiopathic forms of the disease. In some cases, AIN requires a therapeutic action according to a single specific etiology by handling the offending agent and applying an immunosuppressant. Although AIN can be diagnosed through renal biopsy, it is not able to pinpoint the precise cause when multiple causes are suspected to be present simultaneously. Such situations arise when a patient suffering from infection develops AIN during antibiotic therapy, the exact causative factor of which becomes a challenge for the clinicians to determine. This is attributed to the different approaches employed in different etiologies, wherein clinicians are required to maintain the current antibiotic therapy or augment the dose in cases of infection as AIN etiology, without resorting to immunosuppressant therapy as the primary objective is infection killing. In contrast, antibiotics as an etiology for AIN require an alternative drug from the antibiotics group, along with an immunosuppressant. In the interim, delaying the identification of the precise cause may result in interstitial fibrosis and chronic kidney disease. This narrative review highlights certain findings that can be typical of infection-associated ATIN compared with antibiotic-associated ATIN based on clinical history and physical examination, clinical presentation of different antibiotic drug classes, histopathological features, classical and novel biomarkers, serum and urine cytokines and chemokines, cellular biomarkers, and genetic biomarkers. Although these findings cannot provide conclusive and clear recommendations that can be useful in the clinical practice, they can entice researchers to conduct original research on these features to discover clear recommendations.