Fleet R P, Dupuis G, Marchand A, Burelle D, Beitman B D
Montreal Heart Institute, Quebec, Canada.
Ann Behav Med. 1997 Spring;19(2):124-31. doi: 10.1007/BF02883329.
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.
开发并验证一种检测模型，以提高在因胸痛到急诊科就诊的患者中识别惊恐障碍的概率。
通过逻辑回归分析，对180例以胸痛为主诉到急诊科就诊的连续患者，探讨人口统计学、自我报告的心理和疼痛变量作为惊恐障碍存在的预测因素。然后，对按照相同程序招募的212例患者样本进行前瞻性验证该检测模型。
惊恐-场所恐惧症（场所恐惧症认知问卷、场所恐惧症行动量表）、胸痛性质（简短麦吉尔疼痛问卷）、疼痛部位和性别变量是惊恐障碍存在的最佳预测因素。这些变量将84%的胸痛患者正确分类为惊恐障碍和非惊恐障碍类别。模型特性：在惊恐障碍样本患病率为26%时，敏感性59%；特异性93%；阳性预测值75%；阴性预测值87%。该模型在验证阶段将73%的受试者正确分类。
该模型中的量表完成和评分大约需要十分钟。它可能会改善目前医生对因胸痛就诊患者中惊恐障碍的识别。
