THE USE OF BIOSPECTROSCOPY AND MULTIVARIED CLASSIFICATION TECHNIQUES AS A NEW SCREENING TOOL FOR FIBROMYALGIA
Fibromyalgia, spectral analysis, diagnosis, catastrophizing, pain, kinesiophobia
The American College of Rheumatology (ACR) presented in 2010 a consensus for the diagnosis of fibromyalgia (FM). However, it was observed that even with an assessment and diagnosis guide there are many cases of underdiagnosis or misdiagnosis. This is due to the lack of chemical, immunological markers or specific tests for FM detection. This project aims to use biospectroscopy (infrared spectroscopy) and multivariate classification techniques as new technologies for FM diagnostic using only blood plasma as the analytical material. This is a prospective case-control analytical study. For all subjects, a sociodemographic questionnaire, clinical data collection of FM impact, pain, depression and anxiety will be applied; as well as a collection of 3 ml of blood from each participant. Blood plasma will be fingerprinted using vibrational spectra that reflect the cellular biochemical constitution (nucleic acids, carbohydrates, lipids and proteins). We suggest that there may be differences between the infrared spectral patterns that will be calculated and identified by normalizing these patterns to the control group. Benefits of this project include better disease prognosis, more effective treatment, lower associated morbidity, and lower false positive and false negative results. Evidence of the impact of new technologies on early FM detection justifies their adoption as a public health policy, as recommended by the World Health Organization (WHO).