Neuromyelitis optica spectrum inflammatory myelitis: quantitative sensory testing

• Grant number: 14/08204-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2014
• End date: August 31, 2015
• Field of knowledge: Health Sciences - Medicine
• Principal Investigator: Daniel Ciampi Araujo de Andrade
• Grantee: Ediane Arimatéa Silva
• Host Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Chronic pain development is an important cause of suffering and is present among 60 to 70% of patients with medullary lesions. Concerning the inflammatory myelitis, those from neuromyelitis optica spectrum are associated with worse pain and with more refractory treatment than multiple sclerosis. However, there is poor description of chronic pain patterns and of differences between patients with or without chronic pain. In addition, pain mechanisms are poorly known. The Quantitative Sensory Test (QST) evaluates: sensorial perception after thermal and nociceptive stimuli of controlled intensity; A², A´ and C fibers function and its corresponding central pathways. Hence, QST can be used to identify subtle mechanisms in different lesion types. In summary, chronic pain patterns, differences between patients with and without pain, and sensory profile through QST can, in the future, guide a more specific treatment. Objectives: To perform a cross-sectional evaluation of patients diagnosed with neuromyelitis optica spectrum inflammatory myelitis. It compares patients with and without chronic pain and analyses: clinical aspects, thermal (warm and cold) and nociceptive thresholds and intensity of pain after upper threshold thermal stimulus. Methods: Through an individual-based, observational, cross-sectional study, we initially aim a casuistic of 40 patients with neuromyelitis optica spectrum inflammatory myelitis, including two groups of 20 patients (with and without chronic pain). Those groups will be evaluated by neurological physical examination, trigger-points analysis, scales for pain, fatigue, disability, psychological impact and quality of life evaluation, and QST. Statistical analysis: Quantitative variables will be analysed through t-Student test or Mann-Whitney's test in case of non-parametric data, and through t-Student test and variance analysis in case of parametric data. Normal distribution will be tested through Kolmogorov-Smirnoff's test.