#AI reads Urine# Urine-albumin-creatinine ratio-the old kid on a new block

Published 20 March, 2026

A commentary in the European Journal of Preventive Cardiology emphasizes that single urine albumin-to-creatinine ratio (UACR) measurements—commonly used in precision medicine for cardiovascular disease (CVD) risk prediction—fail to capture dynamic changes. Analysis of the Multi-Ethnic Study of Atherosclerosis (MESA) cohort identified distinct UACR trajectories over 5 and 10 years. Persistently elevated or rapidly rising trajectories were significantly linked to higher risks of heart failure, atrial fibrillation, and coronary heart disease, independent of baseline levels; even individuals with initially normal UACR faced elevated risks and showed increased myocardial injury and stress biomarkers.  

As a validated biomarker of systemic endothelial dysfunction and microvascular damage, UACR is measured via convenient spot urine testing and is incorporated into major guidelines (e.g., American Heart Association risk equations, hypertension guidelines). Serial UACR monitoring offers superior prognostic value over single measurements, with advantages of low cost, accessibility, and intervenability. High-risk trajectories were more prevalent among males, non-White individuals, smokers, and those with diabetes or obesity.  

Limitations include unclear clinical identification of trajectories, undefined optimal testing intervals, confounding factors affecting results, and a relatively healthy cohort—necessitating validation in more diverse populations. Overall, serial UACR assessment is a practical tool for CVD risk stratification, with future potential for personalized prevention through integrated multi-biomarker trajectory analysis.

 

Eur J Prev Cardiol. 2026 Feb 9:zwag083. doi: 10.1093/eurjpc/zwag083.

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.

 

For earlier AI Reads Urine articles:

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/

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