The role of symptoms severity, heart rate, and central sensitization for predicting sleep quality in patients with fibromyalgia

Author:

Lima Daniel1,Pacheco-Barrios Kevin12,Slawka Eric1,Camargo Lucas1ORCID,Castelo-Branco Luis1,Cardenas-Rojas Alejandra1,Neto Moacir Silva123,Fregni Felipe1ORCID

Affiliation:

1. Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital, Massachusetts General Hospital, Harvard Medical School , Boston, MA 02141, United States

2. Vicerrectorado de Investigación, Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud, Universidad San Ignacio de Loyola , Lima 15023, Peru

3. Life Checkup—Medicina Esportiva Avançada , Brasilia 70040, Brazil

Abstract

Abstract Background Clinical predictors of sleep quality in patients with fibromyalgia syndrome (FMS) are still unknown. By identifying these factors, we could raise new mechanistic hypotheses and guide management approaches. We aimed to describe the sleep quality of FMS patients and to explore the clinical and quantitative sensory testing (QST) predictors of poor sleep quality and its subcomponents. Methods This study is a cross-sectional analysis of an ongoing clinical trial. We performed linear regression models between sleep quality (Pittsburgh Sleep Quality Index [PSQI]) and demographic, clinical, and QST variables, controlling for age and gender. Predictors for the total PSQI score and its seven subcomponents were found using a sequential modeling approach. Results We included 65 patients. The PSQI score was 12.78 ± 4.39, with 95.39% classified as poor sleepers. Sleep disturbance, use of sleep medications, and subjective sleep quality were the worst subdomains. We found poor PSQI scores were highly associated with symptom severity (FIQR score and PROMIS fatigue), pain severity, and higher depression levels, explaining up to 31% of the variance. Fatigue and depression scores also predicted the subjective sleep quality and daytime dysfunction subcomponents. Heart rate changes (surrogate of physical conditioning) predicted the sleep disturbance subcomponent. QST variables were not associated with sleep quality or its subcomponents. Conclusions Symptom severity, fatigue, pain, and depression (but no central sensitization) are the main predictors of poor sleep quality. Heart rate changes independently predicted the sleep disturbance subdomain (the most affected one in our sample), suggesting an essential role of physical conditioning in modulating sleep quality in FMS patients. This underscores the need for multidimensional treatments targeting depression and physical activity to improve the sleep quality of FMS patients.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Anesthesiology and Pain Medicine,Neurology (clinical),General Medicine

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