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Phenotypic characteristics of patients with chronic widespread pain and fibromyalgia: a cross-sectional cluster analysis.
Duhn, P H; Christensen, R; Locht, H; Henriksen, M; Ginnerup-Nielsen, E; Bliddal, H; Wæhrens, E E; Thielen, K; Amris, K.
Afiliación
  • Duhn PH; The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Christensen R; Department of Rheumatology, Copenhagen University Hospital, Bispebjerg-Frederiksberg Hospital, Frederiksberg, Denmark.
  • Locht H; The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Henriksen M; Research Unit of Rheumatology, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Odense, Denmark.
  • Ginnerup-Nielsen E; Department of Rheumatology, Copenhagen University Hospital, Bispebjerg-Frederiksberg Hospital, Frederiksberg, Denmark.
  • Bliddal H; The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Wæhrens EE; The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Thielen K; The Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Amris K; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
Scand J Rheumatol ; : 1-10, 2024 Jan 26.
Article en En | MEDLINE | ID: mdl-38275145
ABSTRACT

OBJECTIVE:

This study aimed to explore whether phenotypic characteristics of patients with chronic widespread pain (CWP) and fibromyalgia (FM) can be aggregated into definable clusters that may help to tailor treatments.

METHOD:

Baseline variables (sex, age, education, marital/employment status, pain duration, prior CWP/FM diagnosis, concomitant rheumatic disease, analgesics, tender point count, and disease variables derived from standardized questionnaires) collected from 1099 patients (93.4% females, mean age 44.6 years) with a confirmed CWP or FM diagnosis were evaluated by hierarchical cluster analysis. The number of clusters was based on coefficients in the agglomeration schedule, supported by dendrograms and silhouette plots. Simple and multiple regression analyses using all variables as independent predictors were used to assess the likelihood of cluster assignment, reported as odds ratios (ORs) with 95% confidence intervals (CIs).

RESULTS:

Only one cluster emerged (Cluster 1 455 patients). Participants in this cluster were characterized as working (OR 66.67, 95% CI 7.14 to 500.00), with a medium-term/higher education (OR 16.80, 95% CI 1.94 to 145.41), married/cohabiting (OR 14.29, 95% CI 1.26 to 166.67), and using mild analgesics (OR 25.64, 95% CI 0.58 to > 999.99). The odds of being an individual in Cluster 1 were lower when having a worse score on the PDQ (score ≥ 18) (OR < 0.001, 95% CI < 0.001 to 0.02).

CONCLUSION:

We identified one cluster, where participants were characterized by a potentially favourable clinical profile. More studies are needed to evaluate whether these characteristics could be used to guide the management of patients with CWP and FM.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Scand J Rheumatol Año: 2024 Tipo del documento: Article País de afiliación: Dinamarca

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Scand J Rheumatol Año: 2024 Tipo del documento: Article País de afiliación: Dinamarca