Objectives: Widespread pain is important for the diagnosis of fibromyalgia (FM). For this purpose, the sum of pain regions obtained from a topographical distribution has been used to compute a Widespread Pain Index (WPI), but there is no empirical basis for choosing the regions. The aim of this study was to find an empirical distribution of the pain regions.
Materials and methods: We evaluated 228 female patients with FM. They completed the Fibromyalgia Survey Questionnaire, Fibromyalgia Impact Questionnaire (FIQ), Combined Index of Severity in Fibromyalgia (ICAF), and Short Form-36 Health Survey. The pain regions of the WPI were grouped by the topographical distribution (WPIR) and compared with a new empirical distribution (WPIE) obtained through exploratory factor analysis. A decision- tree analysis was conducted to identify the optimal algorithm for selecting pain regions related to the severity of FM.
Results: The WPIE has a normal distribution compared with the WPIR. It also shows higher correlations with FM severity. From the factor analysis, 4 factors explain 48.5% of the variance. Two factors (emotional and physical) can conform to the decision-tree analysis using the dependent variables FIQ and ICAF. These factors are very congruent with the cutoff points previously proposed for FIQ and ICAF. The emotional factor is the first in the decision-tree.
Discussion: WPIE has a normal distribution and shows better predictive qualities than WPIR. The emotional factor is conceptualized as emotional because of the relative importance of the right hemisphere in negative emotions and pain. The physical factor could be responsible for the decreased ability to coordinate left-right stepping.