Identification of resistance in Escherichia coli and Klebsiella pneumoniae using excitation-emission matrix fluorescence spectroscopy and multivariate analysis.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
03 08 2020
03 08 2020
Historique:
received:
01
07
2019
accepted:
09
06
2020
entrez:
5
8
2020
pubmed:
5
8
2020
medline:
7
5
2021
Statut:
epublish
Résumé
Klebsiella pneumoniae and Escherichia coli are part of the Enterobacteriaceae family, being common sources of community and hospital infections and having high antimicrobial resistance. This resistance profile has become the main problem of public health infections. Determining whether a bacterium has resistance is critical to the correct treatment of the patient. Currently the method for determination of bacterial resistance used in laboratory routine is the antibiogram, whose time to obtain the results can vary from 1 to 3 days. An alternative method to perform this determination faster is excitation-emission matrix (EEM) fluorescence spectroscopy combined with multivariate classification methods. In this paper, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), coupled with dimensionality reduction and variable selection algorithms: Principal Component Analysis (PCA), Genetic Algorithm (GA), and the Successive Projections Algorithm (SPA) were used. The most satisfactory models achieved sensitivity and specificity rates of 100% for all classes, both for E. coli and for K. pneumoniae. This finding demonstrates that the proposed methodology has promising potential in routine analyzes, streamlining the results and increasing the chances of treatment efficiency.
Identifiants
pubmed: 32747745
doi: 10.1038/s41598-020-70033-x
pii: 10.1038/s41598-020-70033-x
pmc: PMC7400627
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12994Références
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