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  • Sleep disturbances in fibromyalgia-an Australian tertiary hospital experience

    Author(s)
    Su, Kevin
    Sriram, Krishna Bajee
    Afrasyabi, Parham
    Griffith University Author(s)
    Sriram, Krishna K.
    Year published
    2019
    Metadata
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    Abstract
    Background Fibromyalgia (FM) is a central pain disorder with an estimated population prevalence of 2-7% and six times as common in women than men.1Obstructive sleep apnoea (OSA) is a structural sleep disorder, with an estimated incidence of 14% of males and 5% females. Incidence of OSA in FM has been variably reported but estimated at 25-81%.2 Despite its frequency, the underlying nature of sleep disturbances haven’t been consistently replicated. A 2017 meta-analysis found significant differences in sleep efficiency (SE), a measure of total time spent in REM (Rapid Eye movement) sleep, number of arousals and sleep quality.3 ...
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    Background Fibromyalgia (FM) is a central pain disorder with an estimated population prevalence of 2-7% and six times as common in women than men.1Obstructive sleep apnoea (OSA) is a structural sleep disorder, with an estimated incidence of 14% of males and 5% females. Incidence of OSA in FM has been variably reported but estimated at 25-81%.2 Despite its frequency, the underlying nature of sleep disturbances haven’t been consistently replicated. A 2017 meta-analysis found significant differences in sleep efficiency (SE), a measure of total time spent in REM (Rapid Eye movement) sleep, number of arousals and sleep quality.3 Prados et al in 2013 showed women with FM have less severe sleep disturbance than males, suggesting a gender difference.4 Objectives To identify the incidence of FM in a cohort referred to the respiratory department for diagnostic polysomnography (dPSG) at the Gold Coast University Hospital (GCUH), a tertiary referral centre in Australia. We aim to identify epidemiological, gender differences and sleep abnormalities in patients with FM and OSA. Methods: dPSG reports of 998 patients with 1053 studies at the GCUH from 2015 - 18 was audited. We included FM diagnosed by a rheumatologist from the general Rheumatology clinics of the same facility. Two control groups were formed, one with a random number generator. The second from manual matching of major OSA risk factors such as age, gender and Body mass index (BMI), with a two to one ratio for statistical power. All were subsequently subdivided into gender. Statistical analysis was performed with calculation of mean, standard deviation and T tests for significance as calculated by the computer software Stata.
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    Conference Title
    ANNALS OF THE RHEUMATIC DISEASES
    Volume
    78
    Issue
    Suppl 2
    DOI
    https://doi.org/10.1136/annrheumdis-2019-eular.2534
    Subject
    Clinical sciences
    Immunology
    Science & Technology
    Life Sciences & Biomedicine
    Rheumatology
    Publication URI
    http://hdl.handle.net/10072/392650
    Collection
    • Conference outputs

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