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

Autor: Emily Baker, Hana Coogan, Meaghan Sullivan, Varun Kavuru, Stephanie Lundgren, Giuseppe Orlando, Caitlin Steen, Ben Agnor, Pang Du, Kristen Merrifield, Allan Sklar, Tommy Vu, John L. Robertson, James L. Pirkle, Susan Guelich, Lampros Karageorge, Austin Gouldin, Devasmita Dev, Gabrielle Martinez, William Carswell, Ryan S. Senger
Rok vydání: 2020
Předmět:
Male
Physiology
medicine.medical_treatment
Urine
Spectrum Analysis
Raman
Biochemistry
01 natural sciences
Mathematical and Statistical Techniques
Dialysis Solutions
Chronic Kidney Disease
Medicine and Health Sciences
Statistical Data
Aged
80 and over
Principal Component Analysis
0303 health sciences
Multidisciplinary
medicine.diagnostic_test
Statistics
Middle Aged
Healthy Volunteers
Body Fluids
Data Accuracy
Nephrology
Physical Sciences
symbols
Medicine
Female
Analysis of variance
Anatomy
Peritoneal Dialysis
Research Article
Adult
medicine.medical_specialty
Adolescent
Urinalysis
Science
Urology
Research and Analysis Methods
Sensitivity and Specificity
Peritoneal dialysis
Young Adult
03 medical and health sciences
symbols.namesake
Medical Dialysis
medicine
Metabolomics
Humans
Statistical Methods
End-stage kidney disease
Aged
030306 microbiology
business.industry
010401 analytical chemistry
Biology and Life Sciences
Spectral processing
medicine.disease
0104 chemical sciences
Metabolism
Specimen Preparation and Treatment
Multivariate Analysis
Kidney Failure
Chronic
business
Raman spectroscopy
Mathematics
Biomarkers
Kidney disease
Zdroj: PLoS ONE
PLoS ONE, Vol 15, Iss 1, p e0227281 (2020)
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0227281
Popis: 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.
Databáze: OpenAIRE
Externí odkaz: