Hematocrit (Hct), the volume percent of red cells in blood, is monitored routinely for blood donors, surgical patients, and trauma victims and requires blood to be removed from the patient. An accurate, noninvasive method for directly measuring hematocrit on patients is desired for these applications. The feasibility of noninvasive hematocrit measurement by using near-infrared (NIR) spectroscopy and partial least-squares (PLS) techniques was investigated, and methods of in vivo calibration were examined. Twenty Caucasian patients undergoing cardiac surgery on cardiopulmonary bypass were randomly selected to form two study groups. A fiber-optic probe was attached to the patient's forearm, and NIR spectra were continuously collected during surgery. Blood samples were simultaneously collected and reference Hct measurements were made with the spun capillary method. PLS multivariate calibration techniques were applied to investigate the relationship between spectral and Hct changes. Single patient calibration models were developed with good cross-validated estimation of accuracy (∼ 1 Hct%) and trending capability for most patients. Time-dependent system drift, patient temperature, and venous oxygen saturation were not correlated with the hematocrit measurements. Multi-subject models were developed for prediction of independent subjects. These models demonstrated a significant patient-specific offset that was shown to be partially related to spectrometer drift. The remaining offset is attributed to the large spectral variability of patient tissue, and a significantly larger set of patients would be required to adequately model this variability. After the removal of the offset, the cross-validated estimation of accuracy is 2 Hct%.

Noninvasive monitoring of deep-tissue pH has been demonstrated with the use of near-infrared spectroscopic measurements and the partial least-squares (PLS) multivariate calibration technique. The near-infrared reflectance spectra (700 to 1100 nm) of the teres major muscle in five New Zealand rabbits were obtained in vivo, along with reference pH values in the muscle measured by microelectrodes. The muscle pH was varied by controlling the blood supply to the muscle. PLS analysis with cross-validation techniques, along with several data preprocessing methods, was used to relate the tissue pH to spectra. When multi-subject PLS calibration models were used to predict a new independent subject, a subject-dependent offset was observed. Several strategies for minimizing the subject-dependent offset were discussed. With a baseline subtraction procedure, the subject-dependent offset was minimized to less than 0.1 pH units while the average standard error of prediction (SEP) was close to 0.05 pH units. This result suggests that it is possible to build a single robust calibration model for all new independent subjects. Tissue chemistry during ischemia (blood flow reduction) is different from the chemistry of reperfusion (blood flow restoration), and it was found that separate calibration models permit more accurate prediction of pH.

NIRS determination of small-bowel pH may be a good tool to monitor the adequacy of resuscitation.