Article

PURPOSE: To determine the diagnostic accuracy for single symptoms and clusters of
symptoms to distinguish between individuals with and without chronic fatigue
syndrome (CFS). 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.
RESULTS: 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.
CONCLUSIONS: A cluster of associated symptoms distinguishes between individuals
with and without CFS. Fewer associated symptoms may be necessary to establish a
diagnosis of CFS than currently described.

Langue : ANGLAIS