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Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix)

Ryan S Senger, Meaghan Sullivan, Austin Gouldin, Stephanie Lundgren, Kristen Merrifield, Caitlin Steen, Emily Baker, Tommy Vu, Ben Agnor, Gabrielle Martinez, Hana Coogan, William Carswell, Varun Kavuru, Lampros Karageorge, Devasmita Dev, Pang Du, Allan Sklar, James Pirkle, Susan Guelich, Giuseppe Orlando and John L Robertson

PLOS ONE, 2020, vol. 15, issue 1, 1-12

Abstract: Raman Chemometric Urinalysis (RametrixTM) was used to discern differences in Raman spectra from (i) 362 urine specimens from patients receiving peritoneal dialysis (PD) therapy for end-stage kidney disease (ESKD), (ii) 395 spent dialysate specimens from those PD therapies, and (iii) 235 urine specimens from healthy human volunteers. RametrixTM analysis includes spectral processing (e.g., truncation, baselining, and vector normalization); principal component analysis (PCA); statistical analyses (ANOVA and pairwise comparisons); discriminant analysis of principal components (DAPC); and testing DAPC models using a leave-one-out build/test validation procedure. Results showed distinct and statistically significant differences between the three types of specimens mentioned above. Further, when introducing “unknown” specimens, RametrixTM was able to identify the type of specimen (as PD patient urine or spent dialysate) with better than 98% accuracy, sensitivity, and specificity. RametrixTM was able to identify “unknown” urine specimens as from PD patients or healthy human volunteers with better than 96% accuracy (with better than 97% sensitivity and 94% specificity). This demonstrates that an entire Raman spectrum of a urine or spent dialysate specimen can be used to determine its identity or the presence of ESKD by the donor.

Date: 2020
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DOI: 10.1371/journal.pone.0227281

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