Evidence map›Paper›PMID 39350577›Full record

ArticleMedeniyet medical journal2024

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

Emre Leventoglu, Mustafa Soran

Abstract read
In one paragraph

Article in Medeniyet medical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Emre LeventogluKonya City Hospital, Clinic of Pediatric Nephrology, Konya, Türkiye.ORCID 0000-0002-0504-7911
Mustafa SoranKonya City Hospital, Clinic of Pediatric Nephrology, Konya, Türkiye.ORCID 0000-0001-9735-235X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Acute postinfection glomerulonephritisartificial intelligenceChatGPT

Identifiers

PMID39350577
PMCPMC11572215

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