A DIAGNOSTIC ALGORITHM FOR DISTINGUISHING THE EOSINOPHILIA-MYALGIA-SYNDROME FROM FIBROMYALGIA AND CHRONIC MYOFASCIAL PAIN

Objective. To develop a diagnostic algorithm for the eosinophilia-myal gia syndrome (EMS) that complements the existing case definition. Meth ods. We conducted a retrospective study using data on 59 clinical and laboratory variables from a consecutive referral cohort of 91 patients with EMS meeting the Centers for Disease Control and Prevention case definition. Age and sex matched controls included 93 patients with fib romyalgia and 99 patients with chronic myofascial pain. The study peri od was March 1989 to April 1992. Recursive partitioning was used to cr eate a diagnostic algorithm. Results. In the 283 case patients and con trols with disabling myalgias, 4 differentiating variables identified patients with EMS: extremity edema, leukocyte count > 12.5x 10(9)/1, d yspnea, and absence of arthralgias. These 4 variables form a diagnosti c algorithm that has a sensitivity of 95.6%, a specificity of 96.9%, a nd positive and negative predictive values of 93.5 and 97.9%, respecti vely. Conclusion. This algorithm is practical and can be easily applie d in any medical setting. It also readily distinguishes EMS from other common myalgia syndromes.