Full Papers
Design and validation of a predictive model for determining the risk of developing fibromyalgia
N. Benachi Sandoval1, J. Fernández Solà2, A. Guaita Mateo3, M.P. Navarrete Durán4, L.A. Meneses Urrea5, S. Torres Belmonte6, E. Mañes López7, M. López Poyato8
- Dept. of Public Health, Mental Health and Maternal and Child Health Nursing, University of Barcelona, Spain; Research Group “Health Care (recognised by Colciencias)”, Universidad Santiago de Cali, Colombia; Consorci d’Atenció Primària de Salut Barcelona Esquerra, Barcelona, Spain; Working group of the Central Sensitivity Syndrome Unit, Àrea Integral de Salut Barcelona Esquerra (AISBE), Barcelona, Spain. nbenachi@clinic.cat, nbenachi@ub.edu
- Dept. of Medicine, University of Barcelona, Spain; Central Sensitisation Syndromes Unit, Hospital Clínic of Barcelona; Spanish Society of Central Sensitivity Syndrome (SESSC); Working group of the Central Sensitivity Syndrome Unit, Àrea Integral de Salut Barcelona Esquerra (AISBE), Spain; Expert Committee for Fibromyalgia and Chronic Fatigue Syndrome, Catalan Health Service (CATSALUT), Barcelona, Spain.
- Family and Community Nursing, Institut Català de la Salut, Barcelona, Spain.
- Dept. of Medicine, University of Barcelona; Family and Community Medicine, Consorci d’Atenció Primària de Salut Barcelona Esquerra, Barcelona, Spain.
- Research Group “Health Care (recognised by Colciencias)”, Universidad Santiago de Cali; Dept. of Nursing, Universidad Santiago de Cali, Colombia.
- Consorci d’Atenció Primària de Salut Barcelona Esquerra, Barcelona, Spain.
- Dept. of Nursing, Universitat Autònoma de Barcelona Family and Community Nursing, Institut Català de la Salut, Barcelona; Hospital Clínic of Barcelona, Spain.
- Dept. of Public Health, Mental Health and Maternal and Child Health Nursing, University of Barcelona; Family and Community Nursing, Consorci d’Atenció Primària de Salut Barcelona Esquerra, Barcelona; Association of Family and Community Nursing of Catalonia (AIFICC), Barcelona, Spain.
CER15975
2023 Vol.41, N°6
PI 1238, PF 1247
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PMID: 36622095 [PubMed]
Received: 21/06/2022
Accepted : 29/11/2022
In Press: 02/01/2023
Published: 28/06/2023
Abstract
OBJECTIVES:
Fibromyalgia is a prevalent disease of unknown aetiology and is difficult to diagnose. Despite the availability of the American College of Rheumatology criteria for diagnosis, it continues to be a challenge in the field of primary health care in terms of identifying individuals with susceptibility to developing the disease. The aim of this study is to design and validate a predictive model of fibromyalgia in subjects with a history of chronic pain.
METHODS:
This multicentre observational retrospective cohort study was performed on patients aged >18 years, who visited four primary health centres between 2017 and 2020, with a diagnosis of fibromyalgia or arthritis. The Bootstrapping resampling method was used for the validation of the model.
RESULTS:
A total of 198 subjects with fibromyalgia (93 with osteoarthritis, 20 with other types of arthritis, 4 with rheumatoid arthritis) and 120 without fibromyalgia (116 with osteoarthritis, 23 with other types of arthritis, 7 with rheumatoid arthritis) participated in the study. The predictive factors of the final model were self-reported age at onset of symptoms, first-line family history of neurological diseases, exposure to levels of stress, history of post-traumatic acute emotional stress, and personal history of chronic widespread pain prior to diagnosis, comorbidity, and pharmacological prescription during the year of diagnostic confirmation. The predictive capacity adjusted by Bootstrapping was 0.972 (95% CI: 0.955–0.986).
CONCLUSIONS:
The proposed model showed an excellent predictive capacity. The risk calculator designed from the predictive model allows health professionals to have a useful tool to identify subjects at risk of developing fibromyalgia.
