Urinary creatinine estimation as an important analytical limitation of semi-quantitative albumin-to-creatinine ratio strip testing: a diagnostic accuracy study

Background Albuminuria is a key biomarker for chronic kidney disease and cardiovascular risk. Point-of-care urine albumin-to-creatinine ratio (UACR) testing may improve access to chronic kidney disease screening. However, limited evidence is available regarding the agreement of the individual albumin and creatinine components of semi-quantitative UACR strip tests with quantitative laboratory measurements. Methods We evaluated 400 spot urine specimens using the Dirui H13-Cr semi-quantitative UACR strip and compared results with quantitative immunoturbidimetric UACR measurement performed on a Roche Cobas c503 analyzer. Agreement was assessed using Cohen's kappa coefficients, including category-specific agreement according to the KDIGO A1, A2, A3 albuminuria categories, and diagnostic performance was evaluated using sensitivity, specificity, predictive values, likelihood ratios, and diagnostic odds ratio (DOR). Results Agreement between strip-based and quantitative measurements was substantial for urinary albumin ( κ =0.691; 95% CI, 0.632–0.751) but considerably lower for urinary creatinine ( κ =0.377; 95% CI, 0.331–0.423). Despite this disparity, UACR classification demonstrated substantial agreement ( κ =0.627; 95% CI, 0.541–0.714). The findings suggest that semi-quantitative creatinine estimation is the primary analytical determinant of UACR misclassification. For detection of abnormal albuminuria (UACR ≥30 mg/g), the strip achieved a sensitivity of 83.66% and specificity of 83.22%. The PPV was 89.96% and NPV was 73.91%. Category-specific analysis showed that 131 of 177 A2 specimens (74.0%) were classified as A2 by the strip, whereas 64 of 80 A3 specimens (80.0%) were classified as A2 rather than A3. Conclusion The Dirui H13-Cr strip demonstrated acceptable performance for albuminuria screening. However, semi-quantitative urinary creatinine estimation represented an important analytical limitation affecting UACR classification accuracy. Future development of strip-based UACR technologies should prioritize improved creatinine measurement to enhance diagnostic performance.