Martin Vincent T, Penzien Donald B, Houle Timothy T, Andrew Michael E, Lofland Kenneth R
Division of General Medicine, University of Cincinnati College of Medicine, OH 45267-0535, USA.
Headache. 2005 Oct;45(9):1102-12. doi: 10.1111/j.1526-4610.2005.00234.x.
To determine the operating characteristics and predictive value of abbreviated criteria for the diagnosis of migraine headache.
The International Headache Society (IHS) diagnostic criteria for migraine have been adopted in limited fashion in clinical practice. Primary care physicians in particular deal with innumerable conditions and diagnostic algorithms. Unless the IHS criteria are simplified the recognition of migraine headache in primary care settings will not be apt to improve.
This study was a retrospective analysis of four discrete research databases: headache clinic patients (N = 390), private practice neurology patients (N = 290), college students (N = 99), and community-based patients (N = 784). Physicians and psychologists expert in the diagnostic criteria for migraine headache syndromes conducted a standardized diagnostic interview in all patients (N = 1524). Each was later assigned an IHS headache diagnosis by a previously validated computer-based algorithm. The sensitivity, specificity, positive and negative predictive values, and accuracy were calculated for single- and multiple-variable models of migraine predictors. Optimal models were defined as those with positive likelihood ratios (+LRs) of >4.5 and negative likelihood ratios (-LRs) of <0.25 for the combined population.
The only optimal single-variable model was nausea, which had an overall +LR of 4.8 and -LR of 0.23. None of the two-variable models met criteria for an optimal model. The best of the optimal three-variable models were nausea/photophobia/pulsating (+LR 6.7, -LR 0.23) and nausea/photophobia/worsening with physical activity (+LR 5.9, -LR 0.21). These three models maintained positive predictive values >0.80 in all 4 patient populations and negative predictive values >0.70 in the majority of populations.
The single-variable model of nausea and the three-variable models of nausea/photophobia/worse with exertion and nausea/phonophobia/pulsating can effectively predict migraine in diverse clinical settings. These models however, should only be applied after a careful exclusion of secondary headache disorders.
确定偏头痛诊断简化标准的操作特征及预测价值。
国际头痛协会（IHS）的偏头痛诊断标准在临床实践中的采用程度有限。尤其是初级保健医生要处理无数病症和诊断算法。除非简化IHS标准，否则初级保健环境中偏头痛的识别情况不太可能得到改善。
本研究是对四个独立研究数据库进行的回顾性分析：头痛门诊患者（N = 390）、私人执业神经科患者（N = 290）、大学生（N = 99）和社区患者（N = 784）。偏头痛综合征诊断标准方面的内科医生和心理学家对所有患者（N = 1524）进行了标准化诊断访谈。随后通过先前验证的基于计算机的算法为每位患者指定一个IHS头痛诊断。计算偏头痛预测因子单变量和多变量模型的敏感性、特异性、阳性和阴性预测值以及准确性。最佳模型定义为合并人群中阳性似然比（+LRs）>4.5且阴性似然比（-LRs）<0.25的模型。
唯一的最佳单变量模型是恶心，其总体+LR为4.8，-LR为0.23。双变量模型均未达到最佳模型标准。最佳的三变量模型是恶心/畏光/搏动性头痛（+LR 6.7，-LR 0.23）和恶心/畏光/体力活动时加重（+LR 5.9，-LR 0.21）。这三个模型在所有4个患者群体中阳性预测值均>0.80，在大多数群体中阴性预测值>0.70。
恶心单变量模型以及恶心/畏光/劳累时加重和恶心/畏声/搏动性头痛三变量模型可在不同临床环境中有效预测偏头痛。然而，这些模型仅应在仔细排除继发性头痛障碍后应用。
