Hemodialysis (HD) removes nitrogenous waste products from patients? blood
through a semipermeable membrane along a concentration gradient.
Near-infrared spectroscopy (NIRS) is an underexplored method of monitoring
the concentrations of several molecules that reflect the efficacy of the HD
process in dialysate samples. In this study, we aimed to evaluate NIRS as a
technique for the non-invasive detection of uremic solutes by assessing the
correlations between the spectrum of the spent dialysate and the serum
levels of urea, creatinine, and uric acid. Blood and dialysate samples were
taken from 35 patients on maintenance HD. The absorption spectrum of each
dialysate sample was measured three times in the wavelength range of
700-1700 nm, resulting in a dataset with 315 spectra. The artificial neural
network (ANN) learning technique was used to assess the correlations between
the recorded NIR-absorbance spectra of the spent dialysate and serum levels
of selected uremic toxins. Very good correlations between the NIR-absorbance
spectra of the spent dialysate fluid with serum urea (R=0.91) and uric acid
(R=0.91) and an excellent correlation with serum creatinine (R=0.97) were
obtained. These results support the application of NIRS as a non-invasive,
safe, accurate, and repetitive technique for online monitoring of uremic
toxins to assist clinicians in assessing HD efficiency and individualization
of HD treatments.