Identification of age-specific risk factors for hyperuricemia: a machine learning-driven stratified analysis in health examination cohorts

Identification of age-specific risk factors for hyperuricemia: a machine learning-driven stratified analysis in health examination cohorts

Abstract Background Hyperuricemia (HUA) as a global public health challenge, although its overall epidemiological characteristics have been widely reported, its age-specific risk pattern remains controversial. This study aims to reveal the risk factors of HUA in healthy physical examination populati...

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Bibliographic Details
Main Authors: ChuXia Tan, Yuan Liu, Lijun Li, Ying Li, Pingting Yang, Yinglong Duan, Xingxing Wang, Huiyi Zhang, Jingying Wang, Honglian Zhang
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Hyperuricemia
Age distribution
Machine learning
Health examination
Risk factors
Cross-sectional study
Online Access:https://doi.org/10.1186/s12911-025-03123-3
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https://doi.org/10.1186/s12911-025-03123-3

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