Literature DB >> 15336638

Body pain area and pain-related negative affect predict clinical pain intensity in patients with fibromyalgia.

Roland Staud1, Donald D Price, Michael E Robinson, Charles J Vierck.   

Abstract

UNLABELLED: Patients with fibromyalgia (FM) report widespread chronic musculoskeletal pain. Palpation of 9 paired tender points (TPs) is commonly used for the diagnosis of FM according to criteria specified by the American College of Rheumatology. Although TP palpation can be used to assess deep tissue hypersensitivity, it has failed as a reliable indicator of clinical pain intensity in FM. The sum of local areas of pain (SLAP) obtained from a body pain diagram represents a relevant measure of the spatial extent of clinical pain, a feature most likely important for FM pain. Because spatial summation of pain can be an important determinant of clinical pain intensity, we hypothesized that this measure would predict clinical pain intensity in FM patients. Because pain is strongly associated with negative emotions, we evaluated the relationship of pain-related negative affect (PRNA) with clinical pain intensity in FM. The independent contributions of SLAP, PRNA, and TP count to the variance of clinical pain intensity were assessed in 280 FM patients. Clinical pain intensity of 280 FM patients was measured by using a visual analogue scale. FM patients shaded all painful body areas on body pain diagrams. Dolorimetry was used for TP evaluations. PRNA was assessed with the Medical College of Virginia Pain Questionnaire. Hierarchical linear regression was used to test the association of SLAP, TPs, and PRNA with clinical pain intensity. FM patients' mean visual analogue scale rating (0 to 100) of usual clinical pain was 50.1. Mean SLAP, TP count, and PRNA were 11.4, 16.0, and 44.3, respectively. Hierarchical linear regression analysis identified SLAP, TP count, and PRNA as independent predictors of clinical pain that accounted for 45% of the variance in clinical pain intensity ratings in FM patients. Consistent with the literature, TP count predicted only a small part (4%) of this variance. Our statistical model of body pain areas and negative affect predicts a large portion of the variance of pain intensity in FM. This result suggests that the extent of pain areas and negative emotions are uniquely associated with clinical pain intensity in FM. PERSPECTIVE: The number of painful body areas obtained by body pain diagrams is a better predictor of clinical pain intensity than TPs in FM patients. The combination of painful body areas, TP counts, and PRNA predicts 45% of the clinical pain intensity of FM patients. This finding might be useful for clinical evaluations of FM patients.

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Year:  2004        PMID: 15336638     DOI: 10.1016/j.jpain.2004.05.007

Source DB:  PubMed          Journal:  J Pain        ISSN: 1526-5900            Impact factor:   5.820


  41 in total

1.  Mechanical and heat hyperalgesia highly predict clinical pain intensity in patients with chronic musculoskeletal pain syndromes.

Authors:  Roland Staud; Elizabeth E Weyl; Donald D Price; Michael E Robinson
Journal:  J Pain       Date:  2012-06-26       Impact factor: 5.820

2.  Effects of repeated deployment to Iraq and Afghanistan on the health of New Jersey Army National Guard troops: implications for military readiness.

Authors:  Anna Kline; Maria Falca-Dodson; Bradley Sussner; Donald S Ciccone; Helena Chandler; Lanora Callahan; Miklos Losonczy
Journal:  Am J Public Health       Date:  2009-12-17       Impact factor: 9.308

3.  A Comparison of Fibromyalgia Symptoms in Patients with Healthy versus Depressive, Low and Reactive Affect Balance Styles.

Authors:  Loren L Toussaint; Ann Vincent; Samantha J McAllister; Terry H Oh; Afton L Hassett
Journal:  Scand J Pain       Date:  2014-07-01

4.  Measuring positive and negative affect in older adults over 56 days: comparing trait level scoring methods using the partial credit model.

Authors:  Monica K Erbacher; Karen M Schmidt; Steven M Boker; Cindy S Bergeman
Journal:  J Appl Meas       Date:  2012

5.  Predictors of clinical pain in fibromyalgia: examining the role of sleep.

Authors:  Ryan J Anderson; Christina S McCrae; Roland Staud; Richard B Berry; Michael E Robinson
Journal:  J Pain       Date:  2012-03-03       Impact factor: 5.820

Review 6.  Predictors of clinical pain intensity in patients with fibromyalgia syndrome.

Authors:  Roland Staud
Journal:  Curr Rheumatol Rep       Date:  2004-08       Impact factor: 4.592

7.  Colored Pain Drawing as a Clinical Tool in Differentiating Neuropathic Pain from Non-Neuropathic Pain.

Authors:  Nalini Sehgal; Debra B Gordon; Scott Hetzel; Miroslav Misha Backonja
Journal:  Pain Med       Date:  2021-03-18       Impact factor: 3.750

8.  Self-report of alcohol use for pain in a multi-ethnic community sample.

Authors:  Joseph L Riley; Christopher King
Journal:  J Pain       Date:  2009-09       Impact factor: 5.820

9.  Spatial summation of mechanically evoked muscle pain and painful aftersensations in normal subjects and fibromyalgia patients.

Authors:  Roland Staud; Euna Koo; Michael E Robinson; Donald D Price
Journal:  Pain       Date:  2007-04-24       Impact factor: 6.961

10.  Analgesic and anti-hyperalgesic effects of muscle injections with lidocaine or saline in patients with fibromyalgia syndrome.

Authors:  R Staud; E E Weyl; E Bartley; D D Price; M E Robinson
Journal:  Eur J Pain       Date:  2013-11-05       Impact factor: 3.931

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