TY  - BOOK
AU  - Walitt, Brian
TI  - Understanding the Association of Fatigue With Other Symptoms of Fibromyalgia: Development of a Cluster Model
SN  - 2151-464X
PY  - 2016///
KW  - *Fatigue/di [Diagnosis]
KW  - *Fibromyalgia/di [Diagnosis]
KW  - *Pain Measurement
KW  - *Surveys and Questionnaires
KW  - Adult
KW  - Anxiety/di [Diagnosis]
KW  - Anxiety/px [Psychology]
KW  - Catastrophization
KW  - Chi-Square Distribution
KW  - Cluster Analysis
KW  - Cognition
KW  - Cross-Sectional Studies
KW  - Depression/di [Diagnosis]
KW  - Depression/px [Psychology]
KW  - Fatigue/cl [Classification]
KW  - Fatigue/pp [Physiopathology]
KW  - Fatigue/px [Psychology]
KW  - Female
KW  - Fibromyalgia/cl [Classification]
KW  - Fibromyalgia/pp [Physiopathology]
KW  - Fibromyalgia/px [Psychology]
KW  - Humans
KW  - Male
KW  - Middle Aged
KW  - Prognosis
KW  - Prospective Studies
KW  - Regression Analysis
KW  - Severity of Illness Index
KW  - Sleep
KW  - Sleep Wake Disorders/di [Diagnosis]
KW  - Sleep Wake Disorders/pp [Physiopathology]
KW  - Sleep Wake Disorders/px [Psychology]
KW  - Stress, Psychological/di [Diagnosis]
KW  - Stress, Psychological/px [Psychology]
KW  - Journal Article
KW  - Observational Study
KW  - Research Support, N.I.H., Intramural
KW  - Research Support, Non-U.S. Gov't
N2  - CONCLUSION: Overall, subcluster 1 had more intense symptoms than subcluster 2. FMS symptoms may be categorized into 2 clinical subclusters. These findings have implications for an illness whose diagnosis and management are symptom dependent. A longitudinal study capturing the variability in the symptom experience of FMS subjects is warranted.Copyright © 2016, American College of Rheumatology; METHODS: FMS individuals (n=120, 82% ages 31-60 years, 90% women, 59% white) diagnosed with the 1990 or 2010 American College of Rheumatology diagnostic criteria were enrolled. Participants completed multiple validated self-report questionnaires to measure fatigue, pain, depression, anxiety, pain catastrophizing, daytime sleepiness, cognitive function, and FMS-related polysymptomatic distress. Cluster analysis using SPSS 19.0 and structural equation modeling using AMOS 17.0 were used; OBJECTIVE: To develop a symptoms cluster model that can describe factors of fibromyalgia syndrome (FMS) associated with fatigue severity as reported by the sample and to explore FMS clinical symptom subclusters based on varying symptom intensities; RESULTS: Final structural equation modeling the symptoms cluster model showed good fit and revealed that FMS fatigue was associated with widespread pain, symptoms severity, pain intensity, pain interference, cognitive dysfunction, catastrophizing, anxiety, and depression (chi(2) =121.72 (98df), P > 0.05, chi(2) /df=1.242, comparative fit index=0.982, root mean square error of approximation=0.045). Two distinct clinical symptom subclusters emerged: subcluster 1 (78% of total subjects), defined by widespread pain, unrefreshed waking, and somatic symptoms, and subcluster 2 (22% of total subjects), defined by fatigue and cognitive dysfunction with pain being a less severe and less widespread occurrence
UR  - http://dx.doi.org/10.1002/acr.22626
ER  -