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Diagnostic accuracy of symptoms characterising chronic fatigue syndrome
Disability & Rehabilitation, 09/01/2011
Davenport TE et al. – A cluster of associated symptoms distinguishes between individuals with and without chronic fatigue syndrome (CFS). Fewer associated symptoms may be necessary to establish a diagnosis of CFS than currently described.
Methods- A cohort study was conducted in an exercise physiology laboratory in an academic setting.
- Thirty subjects participated in this study (n == 16 individuals with CFS; n == 14 non–disabled sedentary matched control subjects).
- An open–ended symptom questionnaire was administered 1 week following the second of two maximal cardiopulmonary exercise tests administered 24 h apart.
- Receiver operating characteristics (ROC) curve analysis was significant for failure to recover within 1 day (area under the curve == 0.864, 95%% confidence interval [[CI]]: 0.706–1.00, p == 0.001) but not within 7 days.
- Clinimetric properties of failure to recover within 1 day to predict membership in the CFS cohort were sensitivity 0.80, specificity 0.93, positive predictive value 0.92, negative predictive value 0.81, positive likelihood ratio 11.4, and negative likelihood ratio 0.22.
- Fatigue demonstrated high sensitivity and modest specificity to distinguish between cohorts, while neuroendocrine dysfunction, immune dysfunction, pain, and sleep disturbance demonstrated high specificity and modest sensitivity.
- ROC analysis suggested cut–point of three associated symptoms (0.871, 95%% CI: 0.717–1.00, p < 0.001).
- A significant binary logistic regression model (p < 0.001) revealed immune abnormalities, sleep disturbance and pain accurately classified 92%% of individuals with CFS and 88%% of control subjects.