Your browser doesn't support javascript.
loading
Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix).
Senger, Ryan S; Sullivan, Meaghan; Gouldin, Austin; Lundgren, Stephanie; Merrifield, Kristen; Steen, Caitlin; Baker, Emily; Vu, Tommy; Agnor, Ben; Martinez, Gabrielle; Coogan, Hana; Carswell, William; Kavuru, Varun; Karageorge, Lampros; Dev, Devasmita; Du, Pang; Sklar, Allan; Pirkle, James; Guelich, Susan; Orlando, Giuseppe; Robertson, John L.
Afiliação
  • Senger RS; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Sullivan M; Department of Chemical Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Gouldin A; DialySenors, Inc., Blacksburg, Virginia, United States of America.
  • Lundgren S; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Merrifield K; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Steen C; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Baker E; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Vu T; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Agnor B; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Martinez G; Department of Chemical Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Coogan H; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Carswell W; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Kavuru V; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Karageorge L; Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Dev D; Veteran Affairs Medical Center, Salem, Virginia, United States of America.
  • Du P; Veteran Affairs Medical Center, Salem, Virginia, United States of America.
  • Sklar A; Veteran Affairs Medical Center, Salem, Virginia, United States of America.
  • Pirkle J; Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Guelich S; Lewis-Gale Medical Center, Salem, Virginia, United States of America.
  • Orlando G; Department of Internal Medicine-Nephrology, Wake Forest University Baptist Medical Center, Winston-Salem, North Carolina, United States of America.
  • Robertson JL; Valley Nephrology Associates, Roanoke, Virginia, United States of America.
PLoS One ; 15(1): e0227281, 2020.
Article em En | MEDLINE | ID: mdl-31923235
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Urinálise / Falência Renal Crônica Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS One Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Urinálise / Falência Renal Crônica Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: PLoS One Ano de publicação: 2020 Tipo de documento: Article