Streamlining bacterial infection diagnosis: rapid gram classification using FTIR spectroscopy

Araújo, R.; Ramalhete, L.; Fonseca, T.; von Rekowski, C.; Bento, L.; Calado, Cecília

http://hdl.handle.net/10400.21/17227

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
Streamlining.pdf		903.99 KB	Adobe PDF	Download

Send Feedback

Authors

Abstract(s)

In a hospital setting, diagnosing infections typically involves a complex process that includes the collection of biological samples and growing a culture for organism isolation, followed by its characterization. However, these methods are slow, require multiple steps and are often limited by the need of specialized equipment and skilled personnel. In this preliminary study, it was analysed the serum, by FTIR spectroscopy, of 29 critically ill COVID-19 patients in an ICU. It was analysed the effect of varied preprocessing methods and spectral sub-regions on t-SNE. Through the optimization of SVM models, it was possible to achieve a very good gram predictive model with a sensitivity and specificity of 90 and 89% respectively. As an accurate classification of bacterial strains is crucial to guide effective antimicrobial therapy and prevent the spread of multidrug-resistant bacteria, FTIR spectra, acquired in a simple, economic, and rapid mode, presents therefore the potential for development of new classification methods that would greatly enhance the ability to manage bacterial infections.