Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution

We derived an expression that allows us to compute a lower bound for the number of items with the maximum item score for a given study from the reported mean scale score, the number of reported subjects, and the properties of the fatigue rating scale. Several CFS studies that used the recommended fatigue rating scales were selected from literature and analyzed to verify whether abundant extreme scoring had occurred.Extreme scoring occurred on a large number of the items for all three recommended fatigue rating scales across several studies. The percentage of items with the maximum score exceeded 40% in several cases. The amount of extreme scoring for a certain scale varied from one study to another, which suggests heterogeneity in the selected subjects across studies.Because all three instruments easily reach the extreme ends of their scales on a large number of the individual items, they do not accurately represent the severe fatigue that is characteristic for CFS. This should lead to serious questions about the validity and suitability of the Checklist Individual Strength, the Chalder Fatigue Scale, and the Krupp Fatigue Severity Scale for evaluating fatigue in CFS research.Since ambiguities in the 1994 chronic fatigue syndrome (CFS) research case definition [1] do indeed contribute to inconsistenties in the identification of cases, I welcome the publication by Reeves et al. [2] and the authors' efforts to resolve these problems. However, I have to express my deepest concerns about the three instruments that the authors have recommend for measuring fatigue in research studies on CFS. Because all three instruments easily reach the extreme ends of their scales on a large number of the individual items, they do not accurately represent the severe fatigue that is required to satisfy any of the published CFS research case definitions [1,3-5]. This low ceiling effect seriously distorts the fatigue measurements, which will inevitably result in bias and potentially mislea