Fibromyalgia is a syndrome characterized by chronic and widespread musculoskeletal pain. It is often accompanied by other symptoms such as fatigue, bowel disorders, sleep disturbances, and mood changes. It is estimated that fibromyalgia syndrome (FMS) affects approximately 2% to 8% of the global population.
The American College of Rheumatology (ACR) diagnostic criteria, based on the presence of multiple tender points, widespread chronic pain, somatic symptoms (such as headaches and abdominal pain), and cognitive symptoms, are used to diagnose individuals with fibromyalgia syndrome (FMS). Widespread pain, headaches, muscle spasms, and balance disorders are the most common symptoms leading to physical disability. These disabling symptoms reduce quality of life and make daily activities more difficult. The impact of these symptoms results in an annual cost of €7,256-7,900 per diagnosed patient in developed countries, creating a secondary socioeconomic burden . This burden includes high absenteeism, unemployment, early retirement, and an increased number of sick leave days.
Postural stability is a complex task required to maintain balance and orientation in a gravity-based environment. This task necessitates the rapid and dynamic integration of sensory information from the somatosensory, vestibular, and visual systems, which are essential for maintaining balance. Changes in balance are associated with poor balance confidence, which increases the risk of falls. Balance disorders are among the most common symptoms in patients with fibromyalgia syndrome (FMS), with a prevalence ranging from 45% to 68%. Previous studies have demonstrated that balance disorders are more prevalent in FMS patients compared to healthy individuals. Furthermore, in FMS patients with impaired balance, a correlation has been shown between balance disorders and an increased risk and/or frequency of falls. However, the underlying mechanism of balance problems in these patients has not yet been elucidated.
FMS is known to originate from a central sensitization phenomenon. According to the International Association for the Study of Pain, central sensitization is defined as an increased response of central nervous system (CNS) neurons to normal or subthreshold afferent inputs. It is hypothesized that changes in postural control may be a response to impaired sensory processing within the CNS and that the increased responsiveness of nociceptive neurons and the presence of central sensitization in the CNS may affect postural control processing, altering neuromuscular interactions and disrupting balance.
Central sensitization, one of the key mechanisms in the pathogenesis of FMS, has been reported to play a significant role in balance control in a study conducted by Sennholz et al. on patients with migraines. In this study, which included migraine patients and healthy controls, balance assessment was performed alongside an evaluation of central sensitization using quantitative sensory tests (cold and heat pain thresholds, mechanical pain thresholds, and pressure pain thresholds) and the central sensitization inventory. The results demonstrated that balance impairment in migraine patients was associated with a decreased pain threshold and an increased central sensitization inventory score.
To our knowledge, no study has yet quantitatively investigated the relationship between central sensitization levels and balance performance in FMS. Based on these findings, we aim to determine the relationship between central sensitization parameters and static and dynamic balance changes in FMS, a member of the central sensitivity syndrome family, similar to migraines. Furthermore, we seek to highlight the importance of future rehabilitation interventions targeting this relationship, thereby contributing to the existing literature.
The study will be conducted as an observational, single-center study at the Physical Medicine and Rehabilitation Clinic of Health Sciences University Sultan 2.Abdülhamid Han Training and Research Hospital, involving patients diagnosed with FMS and healthy volunteers.
As part of the study, demographic data including participants' age, gender, height, weight, body mass index, smoking and alcohol use, marital status, occupation, education level, current medications, presence of comorbidities, and duration of FMS diagnosis will be recorded. Patients will be evaluated once, and the assessment will consist of the following:
* Biodex Balance System \[Biodex Balance System SD (Biodex, Inc, Shirley, NY) (BBS)\]
* Quantitative Sensory Testing, including Pressure Pain Threshold Measurement with an Algometer and Conditioned Pain Modulation
* Slowly Repeated Evoked Pain Assessment Protocol
* Central Sensitization Inventory
* Numeric Rating Scale
* Revised Fibromyalgia Impact Questionnaire
* S-LANSS Pain Score
* Tampa Kinesiophobia Scale
* Hospital Anxiety and Depression Scale
* SF-12 Quality of Life Scale
* Fatigue Severity Scale
* Timed Up and Go Test
Number of Patients to be Included in the Study:The number of patients to be included in the study has been planned based on the study by Sennholz et al., published in May 2024, using G-power version 3.1. The study will include 20 healthy controls and 55 fibromyalgia patients.
Statistical Methods:The distribution pattern of the data and the tests to be applied will be determined based on the Kolmogorov-Smirnov test, skewness, and kurtosis values. If the data follow a parametric distribution, they will be presented as mean ± standard deviation and 95% confidence interval; if the data follow a non-parametric distribution, they will be presented as median ± interquartile range (IQR).
Pressure pain threshold measurements with the algometer, conditioned pain modulation measurements, slowly repeated evoked pain measurements, and balance parameters will be compared between the patient and control groups using independent group T-tests or Mann-Whitney U tests. The linear relationships between algometer pressure pain threshold measurements, conditioned pain modulation, slowly repeated evoked pain measurements, and clinical parameters will be examined using Spearman/Pearson correlation analysis. For parametric data, multiple regression models may be constructed based on the characteristics of the variables.
