Detecting panic disorder in emergency department chest pain patients: a validated model to improve recognition.

Abstract

To develop and validate a detection model to improve the probability of recognizing panic disorder in patients consulting the emergency department for chest pain. Through logistic regression analysis, demographic, self-report psychological, and pain variables were explored as factors predictive of the presence of panic disorder in 180 consecutive patients consulting an emergency department with a chief complaint of chest pain. The detection model was then prospectively validated on a sample of 212 patients recruited following the same procedure. Panic-agoraphobia (Agoraphobia Cognitions Questionnaire, Mobility Inventory for Agoraphobia), chest pain quality (Short Form McGill Pain Questionnaire), pain loci, and gender variables were the best predictors of the presence of panic disorder. These variables correctly classified 84% of chest pain subjects in panic and non-panic disorder categories. Model properties: sensitivity 59%; specificity 93%; positive predictive power 75%; negative predictive power 87% at a panic disorder sample prevalence of 26%. The model correctly classified 73% of subjects in the validation phase. The scales in this model take approximately ten minutes to complete and score. It may improve upon current physician recognition of panic disorder in patients consulting for chest pain.