Identification and quantification of ciprofloxacin in urine through excitation-emission fluorescence and three-way PARAFAC calibration

Due to the second-order advantage, calibration models based on parallel factor analysis (PARAFAC) decomposition of three-way data are becoming important in routine analysis. This work studies the possibility of fitting PARAFAC models with excitation-emission fluorescence data for the determination o...

Full description

Saved in:
Bibliographic Details
Published in:Analytica chimica acta 2009-05, Vol.642 (1), p.193-205
Main Authors: Ortiz, M.C., Sarabia, L.A., Sánchez, M.S., Giménez, D.
Format: Article
Language:English
Subjects:
Adult
Analytical chemistry
Anti-Bacterial Agents - urine
Calibration
Chemistry
Ciprofloxacin
Ciprofloxacin - urine
Exact sciences and technology
Female
Fluorescence
Humans
Male
Mesalamine - urine
Parallel factor analysis
Software
Spectrometric and optical methods
Spectrometry, Fluorescence - methods
Urine
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Due to the second-order advantage, calibration models based on parallel factor analysis (PARAFAC) decomposition of three-way data are becoming important in routine analysis. This work studies the possibility of fitting PARAFAC models with excitation-emission fluorescence data for the determination of ciprofloxacin in human urine. The finally chosen PARAFAC decomposition is built with calibration samples spiked with ciprofloxacin, and with other series of urine samples that were also spiked. One of the series of samples has also another drug because the patient was taking mesalazine. The mesalazine is a fluorescent substance that interferes with the ciprofloxacin. Finally, the procedure is applied to samples of a patient who was being treated with ciprofloxacin. The trueness has been established by the regression “predicted concentration versus added concentration”. The recovery factor is 88.3% for ciprofloxacin in urine, and the mean of the absolute value of the relative errors is 4.2% for 46 test samples. The multivariate sensitivity of the fit calibration model is evaluated by a regression between the loadings of PARAFAC linked to ciprofloxacin versus the true concentration in spiked samples. The multivariate capability of discrimination is near 8 μg L −1 when the probabilities of false non-compliance and false compliance are fixed at 5%.
ISSN:0003-2670
1873-4324
DOI:10.1016/j.aca.2009.01.040