von Kodolitsch Y, Schwartz A G, Nienaber C A
Department of Cardiology, University Hospital Eppendorf, Hamburg, Germany.
Arch Intern Med. 2000 Oct 23;160(19):2977-82. doi: 10.1001/archinte.160.19.2977.
Clinical criteria for aortic dissection are poorly defined. Thus, 35% of aortic dissections remain unsuspected in vivo, and 99% of suspected cases can be refuted.
To identify independent predictors of acute aortic dissection and create a prediction model for facilitated estimation of the individual risk of dissection.
Two hundred fifty patients with acute chest pain, back pain, or both; absence of an established differential diagnosis of the pain syndrome; and clinical suspicion of acute aortic dissection were evaluated for the presence of 26 clinical variables in a prospective, observational study. Multivariate analysis was performed to create a prediction model of aortic dissection.
Aortic pain with immediate onset, a tearing or ripping character, or both; mediastinal widening, aortic widening, or both on chest radiography; and pulse differentials, blood pressure differentials, or both (P<.001 for all) were identified as independent predictors of acute aortic dissection. Probability of dissection was low with absence of all 3 variables (7%), intermediate with isolated findings of aortic pain or mediastinal widening (31% and 39%, respectively), and high with isolated pulse or blood pressure differentials or any combination of the 3 variables (> or = 83%). Accordingly, 4% of all dissections were assigned to the low-probability group, 19% to the intermediate-probability group, and 77% to the high-probability group of aortic dissection.
Assessment of 3 clinical variables permitted identification of 96% of the acute aortic dissections and stratification into high-, intermediate-, and low-probability groupings of disease. With better selection for prompt diagnostic imaging, this prediction model can be used as an aid to improve patient care in aortic dissection. Arch Intern Med. 2000;160:2977-2982
主动脉夹层的临床诊断标准尚不明确。因此，35%的主动脉夹层在活体中未被怀疑，99%的疑似病例可被排除。
确定急性主动脉夹层的独立预测因素，并创建一个预测模型，以便更方便地评估个体发生夹层的风险。
在一项前瞻性观察研究中，对250例有急性胸痛、背痛或两者皆有的患者进行评估；疼痛综合征尚无明确的鉴别诊断；临床怀疑为急性主动脉夹层，评估26项临床变量。进行多变量分析以创建主动脉夹层的预测模型。
急性发作的主动脉疼痛，呈撕裂样或撕开样特征，或两者兼具；胸部X线检查显示纵隔增宽、主动脉增宽，或两者皆有；脉搏差异、血压差异，或两者皆有（所有P<0.001）被确定为急性主动脉夹层的独立预测因素。若三项变量均不存在，夹层发生概率较低（7%）；若仅有主动脉疼痛或纵隔增宽单项表现，概率中等（分别为31%和39%）；若仅有脉搏或血压差异，或三项变量的任意组合，概率较高（≥83%）。因此，所有夹层病例中，4%被归为低概率组，19%为中概率组，77%为高概率组。
对三项临床变量的评估可识别96%的急性主动脉夹层病例，并将其分为疾病的高、中、低概率组。通过更好地选择及时的诊断性影像学检查，该预测模型可用于辅助改善主动脉夹层患者的治疗。《美国医学杂志》。2000年；第160卷：2977 - 2982页
