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Gait markers in Fibromyalgia

Friday 18 November 2011

From BMC Musculoskeletal Disorders:


Walking in waterThe interest of gait markers in the identification of subgroups among fibromyalgia patients

Bernard Auvinet email, Denis Chaleil email, Jean Cabane email, Anne Dumolard email, Pierre Hatron email, Robert Juvin email, Michel Lanteri-Minet email, Yves Mainguy email, Laurence Negre-Pages email, Fabien Pillard email, Daniel Riviere email and Yves-Michel Maugars email

BMC Musculoskeletal Disorders 2011, 12:258 doi:10.1186/1471-2474-12-258

Service de Médecine Interne et Thérapeutique, Hôtel Dieu, Université Paris Descartes, INSERM U 987, 1 Place du Parvis Notre Dame, 75004 Paris, France

Unité de Recherche Clinique, Hôpital Lariboisière, 2 Rue Ambroise Paré, 75010 Paris, France

Unité Stress et Anxiété, Hôpital Fontan, CHRU de Lille, 6 Rue André Verhaeghe 59037 Lille Cedex, France

Département d'épidémiologie, Hôtel Dieu, Université Paris Descartes, 1 Place du Parvis Notre Dame, 75004 Paris, France

email author email     email corresponding author email

BMC Musculoskeletal Disorders 2011, 12:224 doi:10.1186/1471-2474-12-258

Published: 11 November 2011


Fibromyalgia (FM) is a heterogeneous syndrome and its classification into subgroups calls for broad-based discussion. FM subgrouping, which aims to adapt treatment according to different subgroups, relies in part, on psychological and cognitive dysfunctions. Since motor control of gait is closely related to cognitive function, we hypothesized that gait markers could be of interest in the identification of FM patients' subgroups. This controlled study aimed at characterizing gait disorders in FM, and subgrouping FM patients according to gait markers such as stride frequency (SF), stride regularity (SR), and cranio-caudal power (CCP) which measures kinesia.

A multicentre, observational open trial enrolled patients with primary FM (44.1+/-8.1y), and matched controls (44.1+/-7.3y). Outcome measurements and gait analyses were available for 52 pairs. A 3-step statistical analysis was carried out. A preliminary single blind analysis using k-means cluster was performed as an initial validation of gait markers. Then in order to quantify FM patients according to psychometric and gait variables an open descriptive analysis comparing patients and controls were made, and correlations between gait variables and main outcomes were calculated. Finally using cluster analysis, we described subgroups for each gait variable and looked for significant differences in self-reported assessments

SF was the most discriminating gait variable (73% of patients and controls). SF, SR, and CCP were different between patients and controls. There was a non-significant association between SF, FIQ and physical components from Short-Form 36 (p=0.06). SR was correlated to FIQ (p=0.01) and catastrophizing (p=0.05) while CCP was correlated to pain (p=0.01). The SF cluster identified 3 subgroups with a particular one characterized by normal SF, low pain, high activity and hyperkinesia. The SR cluster identified 2 distinct subgroups: the one with a reduced SR was distinguished by high FIQ, poor coping and altered affective status.

Gait analysis may provide additional information in the identification of subgroups among fibromyalgia patients. Gait analysis provided relevant information about physical and cognitive status, and pain behavior. Further studies are needed to better understand gait analysis implications in FM.


The above originally appeared here.


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