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Diagnostic Accuracy of Smartphone-Enabled Urinary Albumin-to-Creatinine Ratio Testing
Danielle Jeddah1, Nicholas B Bevins2, Matan Ronen1
1Department of Clinical Development, Healthy.io, Boston, MA, United States.
Background:
Albuminuria is an important biomarker for detecting chronic kidney disease (CKD), particularly in at-risk individuals. Advances in diagnostic technology have introduced home-use, semiquantitative testing methods such as the FDA-cleared Minuteful Kidney Test (MKT). This study compares the diagnostic accuracy of the MKT to the Beckman Coulter AU 480 analyzer, a standard laboratory quantitative method, for detecting albuminuria in individuals with or at risk for CKD.
Methods:
Urine samples were obtained from individuals with risk factors for kidney damage. Each sample was analyzed for the urinary albumin-to-creatinine ratio (uACR) using both the MKT and the laboratory standard method. Albuminuria was classified according to KDIGO guidelines: A1 (uACR <30 mg/g, "normal to mildly increased"), A2 (uACR 30-300 mg/g, "moderately increased"), and A3 (uACR >300 mg/g, "severely increased"). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MKT were calculated against the laboratory standard.
Results:
Out of 615 collected urine samples, 555 met inclusion criteria. Albuminuria (uACR >30 mg/g) was detected in 24.9% of samples using the laboratory method (95% CI: 21.3%-28.5%). The MKT demonstrated a sensitivity of 96.4%, specificity of 84.2%, NPV of 98.6%, and PPV of 66.8%. MKT accurately categorized 85.6% of samples into the KDIGO albuminuria categories A1, A2, and A3, identifying 100% of laboratory-confirmed A3 samples as abnormal.
Conclusions:
The MKT shows high sensitivity, exceeding the guideline-required threshold (>85%, P < 0.001), and acceptable specificity for detecting albuminuria in high-risk populations. This device offers the potential to improve CKD detection and management and facilitate early intervention in primary care and community settings, where accurate rule-out capabilities are essential.
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