Department of General Practice and Family Medicine, University of Marburg, D-35032 Marburg, Germany.
CMAJ. 2010 Sep 7;182(12):1295-300. doi: 10.1503/cmaj.100212. Epub 2010 Jul 5.
Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care.
We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort).
The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%).
The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.
胸痛可由多种情况引起，其中危及生命的心脏疾病最为令人担忧。已经开发出预测评分来排除冠状动脉疾病，以便在急诊环境中使用。我们开发并验证了一种简单的预测规则，用于初级保健。
我们在德国的 74 家初级保健诊所进行了一项横断面诊断研究。初级保健医生招募了所有因胸痛就诊的连续患者（n=1249），并为每位患者记录了症状和发现（推导队列）。一个独立的专家小组审查了在六周和六个月时获得的关于症状、检查、住院和药物治疗的随访数据，以确定是否存在冠状动脉疾病。使用相关变量的调整比值比来开发预测规则。我们使用来自另一项前瞻性初级保健研究的数据（验证队列）来计算不同预测评分截断值的诊断准确性测量值。
预测规则包含五个决定因素（年龄/性别、已知血管疾病、患者认为疼痛来自心脏、疼痛在运动时加重、疼痛不能通过触诊再现），评分范围为 0 至 5 分。推导队列的曲线下面积（接收者操作特征曲线）为 0.87（95%置信区间 [CI] 0.83-0.91），验证队列为 0.90（95% CI 0.87-0.93）。最佳总体区分度是使用 3 分的截断值（阳性结果 3-5 分；阴性结果<或=2 分），其敏感性为 87.1%（95% CI 79.9%-94.2%），特异性为 80.8%（77.6%-83.9%）。
初级保健中用于冠状动脉疾病的预测规则在验证队列中表现稳健。它可以帮助排除在初级保健中因胸痛就诊的患者的冠状动脉疾病。
