Name
Abstract | ||
|---|---|---|
Continuous measurement of lactate levels in the blood is a prerequisite in intensive care patients who are susceptible to sepsis due to their suppressed immune system and increased metabolic demand. Currently, there exists no noninvasive tool for continuous measurement of lactate in clinical practice. The current mode of measurement is based on arterial blood gas analyzers which require sampling of arterial blood. In this work, we propose the use of Near Infra-Red (NIR) spectroscopy together with multivariate models as a means to non-invasively predict the concentration of lactate in the blood. As the first step towards this objective, we examined the possibility of accurately predicting concentrations of sodium lactate (NaLac) from the NIR spectra of 37 isotonic phosphate buffer saline (PBS) samples containing NaLac ranging from 0 to 20 mmol/L. NIR spectra of PBS samples were collected using the Lambda 1050 dual beam spectrometer over a spectral range of 800 - 2600 nm with a quartz cell of 1 mm optical path. Estimates and calibration of the lactate concentration with the NIR spectra were made using Partial Least-Squares (PLS) regression analysis and leave-one-out cross-validation on filtered spectra. The regression analysis showed a correlation coefficient of 0.977 and a standard error of 0.89 mmol/L between the predicted and prepared samples. The results suggest that NIR spectroscopy together with multivariate models can be a valuable tool for non-invasive assessment of blood lactate concentrations. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857756 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Correlation coefficient,Computer vision,Arterial blood,Computer science,Near-infrared spectroscopy,Sodium,Artificial intelligence,Sodium lactate,Chromatography,Spectroscopy,Intensive care,Absorption (pharmacology) | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karthik Budidha | 1 | 0 | 1.01 |
| Mohammadhossein Mamouei | 2 | 0 | 1.01 |
| Nystha Baishya | 3 | 0 | 1.01 |
| Pankaj Vadgama | 4 | 0 | 0.34 |
| P A Kyriacou | 5 | 20 | 16.60 |