#AI reads Urine #Unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome
Published 24 April, 2025
This article focuses on the research of interstitial cystitis/bladder pain syndrome. This disease is characterized by bladder pain, frequent urination, and urgency, which seriously affects the quality of life of patients. It is divided into two types: with Hunner lesions and without Hunner lesions. The pathologies and treatment strategies of the two types are different, but currently, there are no effective diagnostic markers.
The study collected urine samples from 138 patients (116 with Hunner lesions and 22 without Hunner lesions) and 71 control subjects. The levels of 413 lipids in the urine were measured by liquid chromatography-mass spectrometry and adjusted to urinary creatinine levels. The study found that 218 lipids were significant. In the single lipid analysis, C24 ceramide had a good effect in distinguishing patients with Hunner lesions from other groups, and LPC (14:0) had a good effect in distinguishing patients without Hunner lesions from the control group. The paired lipid analysis further improved the discrimination accuracy, and the machine learning model combined with lipid data and patient information had a higher diagnostic accuracy.
However, the study has limitations such as inconsistent urine sample collection time and a small number of patients without Hunner lesions. Overall, the C24 ceramide - related indicators in urine may be used as potential diagnostic markers, and the combination of machine learning and urinary lipidomics is of great significance in future diagnoses.
World J Urol. 2025 Apr 18;43(1):233. doi: 10.1007/s00345-025-05628-y.
Youhe Gao
Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.
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