Diagnostic factors in pediatric primary headache

Abstract Primary headaches are frequent in children. They are difficult to diagnose because there is much disagreement about the interpretation of the historical data and the use of signs and/or symptoms in diagnosis. It would be useful, therefore, to standardize this procedure. We used linear discriminant analysis to determine a classification rule capable of diagnosing new cases of chronic and recurrent primary headache in children. We considered 23 symptoms in 118 patients. Through discriminant analysis we chose five variables: frequency of the attacks, type of pain, neurologic deficits, nausea, and vomiting. With this classification rule, we obtained a total correct classification of 84.7% for migraine, psychogenic headache, and non-defined headache in respect to the diagnoses formulated by a pediatrician and a child neuropsychiatrist after 3 months of follow-up. Our method for diagnosing migraine has a sensitivity of 95% and a specificity of 100%. The algorithm, validated on another 105 pediatric patients, produced a total correct result of 82.9%.