Predictive and prognostic performance of urinary albumin-to-creatinine ratio for acute kidney injury: a systematic review and meta-analysis
Issued Date
2026-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-105033286966
Pubmed ID
41673099
Journal Title
Scientific Reports
Volume
16
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.16 No.1 (2026)
Suggested Citation
Kitisin N., Ismail J., Raykateeraroj N., Hikasa Y., Caroli A., Nübel J., Eastwood G., Bellomo R., Neto A.S. Predictive and prognostic performance of urinary albumin-to-creatinine ratio for acute kidney injury: a systematic review and meta-analysis. Scientific Reports Vol.16 No.1 (2026). doi:10.1038/s41598-026-37717-2 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115945
Title
Predictive and prognostic performance of urinary albumin-to-creatinine ratio for acute kidney injury: a systematic review and meta-analysis
Corresponding Author(s)
Other Contributor(s)
Abstract
The urine albumin-to-creatinine ratio (UACR) is a well-established marker for chronic kidney disease, but its utility in predicting acute kidney injury remains uncertain. This systematic review and meta-analysis aimed to evaluate predictive performance for AKI development and prognostic performance for AKI progression in hospitalized adults. A comprehensive search of Ovid MEDLINE, Embase, and CENTRAL databases identified 13 studies (n = 10,438) on AKI incidence and three studies (n = 1596) on AKI progression. Elevated UACR was associated with an increased risk of AKI (pooled OR 1.39; 95% CI 1.08–1.79) and AKI progression (pooled OR 3.76; 95% CI 2.59–5.45). The pooled sensitivity and specificity for AKI prediction were 0.71 (95% CI 0.59–0.80) and 0.67 (95% CI 0.56–0.76), respectively, with an area under the curve (AUC) of 0.74. However, there was high heterogeneity across studies, and UACR thresholds for AKI prediction varied widely. Despite these limitations, UACR appears to be a promising, low-cost biomarker for predicting AKI, particularly in high-risk settings such as cardiac surgery. Standardization of thresholds and further validation are needed to support its clinical implementation.