Mailing address:
PO Box 322,
Modbury North,
South Australia 5092
Phone:
1300 128 339
Office Hours:
Monday - Friday,
10am - 4pm
(phone)
ME/CFS South Australia Inc supports the needs of sufferers of Myalgic Encephalomyelitis, Chronic Fatigue Syndrome and related illnesses. We do this by providing services and information to members.
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The interest of gait markers in the identification of subgroups among fibromyalgia patients
Bernard Auvinet, Denis Chaleil, Jean Cabane, Anne Dumolard, Pierre Hatron, Robert Juvin, Michel Lanteri-Minet, Yves Mainguy, Laurence Negre-Pages, Fabien Pillard, Daniel Riviere and Yves-Michel Maugars
1 Service de Médecine Interne et Thérapeutique, Hôtel Dieu, Université Paris Descartes, INSERM U 987, 1 Place du Parvis Notre Dame, 75004 Paris, France
2 Unité de Recherche Clinique, Hôpital Lariboisière, 2 Rue Ambroise Paré, 75010 Paris, France
3 Unité Stress et Anxiété, Hôpital Fontan, CHRU de Lille, 6 Rue André Verhaeghe 59037 Lille Cedex, France
4 Département d'épidémiologie, Hôtel Dieu, Université Paris Descartes, 1 Place du Parvis Notre Dame, 75004 Paris, France
Background
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.
Methods
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
Results
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.
Conclusion
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.
Registered Charity 3104
Email:
sacfs@sacfs.asn.au
Mailing address:
PO Box 322,
Modbury North,
South Australia 5092
Phone:
1300 128 339
Office Hours:
Monday - Friday,
10am - 4pm
(phone)