PO:29:132 | Autonomic Dysfunction in Fibromyalgia: A Cross-Sectional Study and Cluster Analysis of Clinical Phenotypes

Sergio Del Vescovo¹, Vincenzo Venerito¹, Maria Giannotta¹, Marco Fornaro¹, Greta Giulia Dipietrangelo¹, Andrea Cito¹, Maria Morrone¹, Giuseppe Lopalco¹, Florenzo Iannone¹ | ¹UOC Reumatologia, Policlinico di Bari, DiMePre-J Bari, Italy

Aim. Fibromyalgia is a chronic condition characterized by widespread pain, fatigue, sleep disturbances and cognitive impairment. Our aim was to characterize autonomic dysfunction in patients meeting the 2016 ACR criteria for fibromyalgia and identify distinct clinical phenotypes. Materials and

Methods. A cross-sectional study on 3.000 voluntary subjects was conducted. Participants completed questionnaires assessing 2016 ACR criteria and the Composite Autonomic Symptom Score (COMPASS-31). Demographic data, lifestyle factors and comorbidities were collected. Descriptive statistics, group comparisons, correlation and logistic regression were performed to examine factors related with fibromyalgia. FAMD was applied for both continuous and categorical variables followed by standardization and K-means clustering on fibromyalgia subject.

Results. Patients with fibromyalgia demonstrated markedly higher autonomic dysfunction compared to non-fibromyalgia subjects (COMPASS-31: 48.23±17.84 vs. 17.13±13.13, p<0.0001). All autonomic domains were significantly affected in fibromyalgia, with the greatest differences in orthostatic intolerance, gastrointestinal and secretomotor functions (Tab.1). Correlation analysis revealed positive associations between fibromyalgia parameters and autonomic dysfunction metrics (all p<0.0001, Fig.1): the SS showed strong correlation with COMPASS-31 score (r=0.63), with moderate associations between SS components and orthostatic intolerance (r=0.40). WPI demonstrated moderate correlation with overall autonomic dysfunction (r=0.54) and orthostatic intolerance (r=0.45). Sex-stratified multivariate logistic regression models showed that COMPASS-31 score was associated with fibromyalgia in females (OR=1.11, 95%CI 1.09-1.13, p<0.0001) and males (OR=1.14, 95%CI 1.08-1.21, p<0.0001), independently of age, BMI, smoking status, sleep duration, family history, and menstrual cycle status. Cluster analysis (Tab.2) revealed 4 clusters: Cluster 0, young patients with moderate WPI but high SS and significant autonomic dysfunction (58.9±3.3), characterized by high rates of smokers and poor sleep quality; Cluster 1, youngest group with lowest BMI, moderate WPI but the lowest SS and autonomic dysfunction (35.5±2.3), with the best sleep parameters; Cluster 2, oldest patients with the highest BMI and highest female predominance, moderate WPI levels, SS scores, and autonomic dysfunction (43.7±1.8), with high rates of menopause and physical inactivity; Cluster 3, middle-aged patients exhibiting the most severe phenotype with highest WPI, SS scores and autonomic dysfunction (63.8±2.3, with high orthostatic intolerance scores), poorest sleep quality and high family history of fibromyalgia.

Discussion. This study provides evidence of significant autonomic dysfunction in fibromyalgia, with higher COMPASS-31 scores across autonomic domains compared to non-fibromyalgia subjects. Our cluster analysis identified 4 distinct phenotypes: the most severe phenotype (Cluster 3) exhibited the highest autonomic dysfunction alongside worst pain, sleep quality, and symptom severity; this was associated with high rates of family history, suggesting genetic influence.