| Autor: |
Passos, João Octávio Sales, dos Santos Alves, Marcelo Victor, Morais, Camilo L. M., Martin, Francis L., Cavalcante, Antônio Felipe, Lemos, Telma Maria Araújo Moura, Moura, Shayanne, Freitas, Daniel L. D., Mariz, João Vitor Medeiros, Carvalho, Jean Lucas, Lima, Kássio M. G., Pegado, Rodrigo |
| Předmět: |
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| Zdroj: |
Scientific Reports; 7/16/2020, Vol. 10 Issue 1, p1-8, 8p |
| Abstrakt: |
Fibromyalgia is a rheumatologic condition characterized by multiple and chronic body pain, and other typical symptoms such as intense fatigue, anxiety and depression. It is a very complex disease where treatment is often made by non-medicated alternatives in order to alleviate symptoms and improve the patient's quality of life. Herein, we propose a method to detect patients with fibromyalgia (n = 252, 126 controls and 126 patients with fibromyalgia) through the analysis of their blood plasma using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques, hence, providing a low-cost, fast and accurate diagnostic approach. Different chemometric algorithms were tested to classify the spectral data; genetic algorithm with linear discriminant analysis (GA-LDA) achieved the best diagnostic results with a sensitivity of 89.5% in an external test set. The GA-LDA model identified 24 spectral wavenumbers responsible for class separation; amongst these, the Amide II (1,545 cm−1) and proteins (1,425 cm−1) were identified to be discriminant features. These results reinforce the potential of ATR-FTIR spectroscopy with multivariate analysis as a new tool to screen and detect patients with fibromyalgia in a fast, low-cost, non-destructive and minimally invasive fashion. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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