Multivariate classifcation techniques and mass spectrometry as a tool in the screening of patients with fIbromyalgia
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2021
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Fibromyalgia is a rheumatological disorder that causes chronic pain and other symptomatic conditions
such as depression and anxiety. Despite its relevance, the disease still presents a complex diagnosis
where the doctor needs to have a correct clinical interpretation of the symptoms. In this context,
it is valid to study tools that assist in the screening of this disease, using chemical work techniques
such as mass spectroscopy. In this study, an analytical method is proposed to detect individuals with
fbromyalgia (n= 20, 10 control samples and 10 samples with fbromyalgia) from blood plasma samples
analyzed by mass spectrometry with paper spray ionization and subsequent multivariate classifcation
of the spectral data (unsupervised and supervised), in addition to the treatment of selected variables
with possible associations with metabolomics. Exploratory analysis with principal component analysis
(PCA) and supervised analysis with successive projections algorithm with linear discriminant analysis
(SPA-LDA) showed satisfactory results with 100% accuracy for sample prediction in both groups. This
demonstrates that this combination of techniques can be used as a simple, reliable and fast tool in the
development of clinical diagnosis of Fibromyalgia.
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ALVES, Marcelo V. S. et al. Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia. Scientific Reports, London, v. 11, e22625, 2021. DOI: 10.1038/s41598-021-02141-1. Disponível em: https://www.nature.com/articles/s41598-021-02141-1. Acesso em: 21 jun. 2023.