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Bayesian Linear Regressions Applied to Fibromyalgia Syndrome for Understanding the Complexity of This Disorder

Author

Listed:
  • Margarita I. Cigarán-Méndez

    (Department of Psychology, Universidad Rey Juan Carlos, 28922 Alcorcón, Spain)

  • Oscar J. Pellicer-Valero

    (Intelligent Data Analysis Laboratory, Department of Electronic Engineering, ETSE (Engineering School), Universitat de València, 46100 Valencia, Spain)

  • José D. Martín-Guerrero

    (Intelligent Data Analysis Laboratory, Department of Electronic Engineering, ETSE (Engineering School), Universitat de València, 46100 Valencia, Spain)

  • Umut Varol

    (VALTRADOFI Research Group, Department of Physiotherapy, Faculty of Health, Camilo Jose Cela University, 28962 Villanueva de la Cañada, Spain)

  • César Fernández-de-las-Peñas

    (Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine, Universidad Rey Juan Carlos, 28922 Alcorcón, Spain)

  • Esperanza Navarro-Pardo

    (Department of Developmental and Educational Psychology, Universitat de València, 46010 Valencia, Spain)

  • Juan A. Valera-Calero

    (VALTRADOFI Research Group, Department of Physiotherapy, Faculty of Health, Camilo Jose Cela University, 28962 Villanueva de la Cañada, Spain
    Department of Physiotherapy, Faculty of Health, Camilo Jose Cela University, 28692 Villanueva de la Cañada, Spain)

Abstract

A better understanding of the connection between factors associated with pain sensitivity and related disability in people with fibromyalgia syndrome may assist therapists in optimizing therapeutic programs. The current study applied mathematical modeling to analyze relationships between pain-related, psychological, psychophysical, health-related, and cognitive variables with sensitization symptom and related disability by using Bayesian Linear Regressions (BLR) in women with fibromyalgia syndrome (FMS). The novelty of the present work was to transfer a mathematical background to a complex pain condition with widespread symptoms. Demographic, clinical, psychological, psychophysical, health-related, cognitive, sensory-related, and related-disability variables were collected in 126 women with FMS. The first BLR model revealed that age, pain intensity at rest (mean-worst pain), years with pain (history of pain), and anxiety levels have significant correlations with the presence of sensitization-associated symptoms. The second BLR showed that lower health-related quality of life and higher pain intensity at rest (mean-worst pain) and pain intensity with daily activities were significantly correlated with related disability. These results support an application of mathematical modeling for identifying different interactions between a sensory (i.e., Central Sensitization Score) and a functional (i.e., Fibromyalgia Impact Questionnaire) aspect in women with FMS.

Suggested Citation

  • Margarita I. Cigarán-Méndez & Oscar J. Pellicer-Valero & José D. Martín-Guerrero & Umut Varol & César Fernández-de-las-Peñas & Esperanza Navarro-Pardo & Juan A. Valera-Calero, 2022. "Bayesian Linear Regressions Applied to Fibromyalgia Syndrome for Understanding the Complexity of This Disorder," IJERPH, MDPI, vol. 19(8), pages 1-12, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4682-:d:792769
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    References listed on IDEAS

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    1. David B. Dunson & Brian Neelon, 2003. "Bayesian Inference on Order-Constrained Parameters in Generalized Linear Models," Biometrics, The International Biometric Society, vol. 59(2), pages 286-295, June.
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    Cited by:

    1. Juan Antonio Valera-Calero & César Fernández-de-las-Peñas & Marcos José Navarro-Santana & Gustavo Plaza-Manzano, 2022. "Efficacy of Dry Needling and Acupuncture in Patients with Fibromyalgia: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(16), pages 1-32, August.

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