OBJECTIVE: To pilot methodologies designed to critically assess the American College of Rheumatology's (ACR) diagnostic criteria for fibromyalgia. DESIGN: Prospective, psychophysical testing. SETTING: An urban teaching hospital. SUBJECTS: Twenty-five patients with fibromyalgia and 31 healthy controls (convenience sample). INTERVENTIONS: Pressure pain threshold was determined at the 18 ACR tender points and five sham points using an algometer (dolorimeter). OUTCOME MEASURES: The patients "algometric total scores" (sums of the patients' average pain thresholds at the 18 tender points) were derived, as well as pain thresholds across sham points. RESULTS: The "algometric total score" could differentiate patients with fibromyalgia from normals with an accuracy of 85.7% (P < 0.001). Even a single tender point had a diagnostic accuracy between 75% and 89%. Although fibromyalgics had less pain across sham points than across ACR tender points, sham points also could be used for diagnosis (85.7%; Ps < 0.001). Hierarchical cluster analysis showed that three points could be used for a classification accuracy equivalent to the use of all 18 points. CONCLUSIONS: There was a significant difference in the "algometric total score" between patients with fibromyalgia and controls, and we suggest this quantified (although subjective) approach may represent a significant improvement over the current diagnostic scheme, but this must be tested vs other painful conditions. The points specified by the ACR were only modestly superior to sham points in making the diagnosis. Most importantly, this pilot suggests single points, smaller groups of points, or sham points may be as effective in diagnosing fibromyalgia as the use of all 18 points, and suggests methodologies to definitively test that hypothesis.
OBJECTIVE: To pilot methodologies designed to critically assess the American College of Rheumatology's (ACR) diagnostic criteria for fibromyalgia. DESIGN: Prospective, psychophysical testing. SETTING: An urban teaching hospital. SUBJECTS: Twenty-five patients with fibromyalgia and 31 healthy controls (convenience sample). INTERVENTIONS: Pressure pain threshold was determined at the 18 ACR tender points and five sham points using an algometer (dolorimeter). OUTCOME MEASURES: The patients "algometric total scores" (sums of the patients' average pain thresholds at the 18 tender points) were derived, as well as pain thresholds across sham points. RESULTS: The "algometric total score" could differentiate patients with fibromyalgia from normals with an accuracy of 85.7% (P < 0.001). Even a single tender point had a diagnostic accuracy between 75% and 89%. Although fibromyalgics had less pain across sham points than across ACR tender points, sham points also could be used for diagnosis (85.7%; Ps < 0.001). Hierarchical cluster analysis showed that three points could be used for a classification accuracy equivalent to the use of all 18 points. CONCLUSIONS: There was a significant difference in the "algometric total score" between patients with fibromyalgia and controls, and we suggest this quantified (although subjective) approach may represent a significant improvement over the current diagnostic scheme, but this must be tested vs other painful conditions. The points specified by the ACR were only modestly superior to sham points in making the diagnosis. Most importantly, this pilot suggests single points, smaller groups of points, or sham points may be as effective in diagnosing fibromyalgia as the use of all 18 points, and suggests methodologies to definitively test that hypothesis.
Authors: Ana Assumpção; Alane B Cavalcante; Cristina E Capela; Juliana F Sauer; Suellen D Chalot; Carlos A B Pereira; Amélia P Marques Journal: BMC Musculoskelet Disord Date: 2009-06-08 Impact factor: 2.362
Authors: W Michael Hooten; Jolene M Smith; Jason S Eldrige; David A Olsen; W David Mauck; Susan M Moeschler Journal: J Pain Res Date: 2014-05-03 Impact factor: 3.133