Clinical Characteristics of Children with Acute Post-Streptococcal Glomerulonephritis and Re-Evaluation of Patients with Artificial Intelligence

Abstract

Objective: Acute post-streptococcal glomerulonephritis (APSGN) is a common cause of acute glomerulonephritis in children. The condition may present as acute nephritic and/or nephrotic syndrome and rarely as rapidly progressive glomerulonephritis. ChatGPT (OpenAI, San Francisco, California, United States of America) has been developed as a chat robot supported by artificial intelligence (AI). In this study, we evaluated whether AI can be used in the follow-up of patients with APSGN. Methods: The clinical characteristics of patients with APSGN were noted from patient records. Twelve questions about APSGN were directed to ChatGPT 3.5. The accuracy of the answers was evaluated by the researchers. Then, the clinical features of the patients were transferred to ChatGPT 3.5 and the follow-up management of the patients was examined. Results: The study included 11 patients with an average age of 9.08±3.96 years. Eight (72.7%) patients had elevated creatinine and 10 (90.9%) had hematuria and/or proteinuria. Anti-streptolysin O was high in all patients (955±353 IU/mL) and C3 was low in 9 (81.8%) patients (0.56±0.34 g/L). Hypertensive encephalopathy, nephrotic syndrome, and rapidly progressive glomerulonephritis were observed in three patients. Normal creatinine levels were achieved in all patients. Questions assessing the definition, epidemiologic characteristics, pathophysiologic mechanisms, diagnosis, and treatment of APSGN were answered correctly by ChatGPT 3.5. All patients were diagnosed with APSGN, and the treatment steps applied by clinicians were similarly recommended by ChatGPT 3.5. Conclusions: The insights and recommendations offered by ChatGPT for patients with APSGN can be an asset in the care and management of patients. With AI applications, clinicians can review treatment decisions and create more effective treatment plans.

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