期刊
LASERS IN MEDICAL SCIENCE
卷 31, 期 7, 页码 1415-1423出版社
SPRINGER LONDON LTD
DOI: 10.1007/s10103-016-2003-y
关键词
Raman spectroscopy; Urea; Creatinine; Human serum; Partial least squares (PLS); Principal components analysis (PCA)
资金
- Sao Paulo Research Foundation (FAPESP) [2009/01788-5]
- Fundacao Esperanca [05/2012]
- Laboratorio Celso Matos
Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based onpartial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.
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