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风湿性多肌痛中巨细胞动脉炎的危险因素及预测模型

Risk factors and predictive models of giant cell arteritis in polymyalgia rheumatica.

作者信息

Rodriguez-Valverde V, Sarabia J M, González-Gay M A, Figueroa M, Armona J, Blanco R, Fernández-Sueiro J L, Martínez-Taboada V M

机构信息

Rheumatology Division, Hospital Universitario M. Valdecilla, Santander, Spain.

出版信息

Am J Med. 1997 Apr;102(4):331-6. doi: 10.1016/s0002-9343(97)00117-4.

Abstract

OBJECTIVE

To identify in polymyalgia rheumatica the best set of predictors for a positive temporal artery biopsy and to define predictive models with either a high or low probability of giant cell arteritis (GCA).

PATIENTS AND METHODS

Retrospective study of 227 patients, 137 with polymyalgia rheumatica unassociated with arteritis (group A) and 90 with polymyalgia associated with biopsy-proven giant cell arteritis (group B or training set). Data on demographic features, clinical and laboratory abnormalities were collected. Risk factors for arteritis were estimated by nonlinear logistic regressions. Simple predictive models were constructed with those predictors more related to arteritis by multivariable analysis. These models were then tested in group B and in 89 cases of arteritis without polymyalgia rheumatica (group C or test set).

RESULTS

The best predictors of arteritis were a new headache odds ratio (OR) 13.6 (95% confidence interval [CI] 4.7 to 39.3); age at onset < 70 years OR 0.11 (CI 0.04 to 0.35); abnormal temporal arteries OR 4.2 (CI 1.3 to 13.7); raised liver enzymes OR 2.9 (CI 1.1 to 7.8), and jaw claudication OR 4.8 (CI 1.0 to 22.7). Amaurosis was only observed in patients with arteritis. Three subsets had a very high risk of arteritis: (1) Patients with recent headache, abnormal arteries, and > or = 70 years at disease onset: sensitivity 44%, positive predictive value (PPV) 93%, likelihood ratio (LR) 20.3; (2) patients with a new headache, jaw claudication, and abnormal arteries: sensitivity 34.4%, PPV 96.9%, LR 47.2; and (3) those, that in addition to the last 3 features, were > or = 70 years of age at disease onset: sensitivity 26.7%, PPV 100%. We could also identify a subset with a very low risk of arteritis constituted by patients < 70 years, without headache, and with clinically normal temporal arteries: sensitivity 1.1%, PPV 1.7%, LR 0.03. In group C or the test set, these four predictive models correctly identified 57.3%, 29.2%, 23.6, and 3.4% of patients, respectively.

CONCLUSIONS

In polymyalgia rheumatica it is feasible to identify subsets with a very high likelihood of GCA. Although in some of these subsets the diagnosis of arteritis is almost certain, we suggest that even then it should be confirmed by temporal artery biopsy. By contrast, in those patients with polymyalgia < 70 years and without cranial features of giant cell arteritis, the risk of vasculitis is so low that the biopsy could be initially avoided and the patient treated with low-dose corticosteroids.

摘要

目的

在风湿性多肌痛中确定颞动脉活检阳性的最佳预测指标集,并定义巨细胞动脉炎(GCA)高概率或低概率的预测模型。

患者与方法

对227例患者进行回顾性研究,其中137例为不伴有动脉炎的风湿性多肌痛患者(A组),90例为经活检证实伴有巨细胞动脉炎的风湿性多肌痛患者(B组或训练集)。收集了人口统计学特征、临床和实验室异常的数据。通过非线性逻辑回归估计动脉炎的危险因素。通过多变量分析,用那些与动脉炎相关性更强的预测指标构建简单的预测模型。然后在B组和89例无风湿性多肌痛的动脉炎病例(C组或测试集)中对这些模型进行测试。

结果

动脉炎的最佳预测指标为新发头痛比值比(OR)13.6(95%置信区间[CI]4.7至39.3);发病年龄<70岁,OR 0.11(CI 0.04至0.35);颞动脉异常,OR 4.2(CI 1.3至13.7);肝酶升高,OR 2.9(CI 1.1至7.8),以及颌部间歇性运动障碍,OR 4.8(CI 1.0至22.7)。黑矇仅在动脉炎患者中观察到。有三个亚组动脉炎风险非常高:(1)近期头痛、动脉异常且发病年龄≥70岁的患者:敏感性44%,阳性预测值(PPV)93%,似然比(LR)20.3;(2)新发头痛、颌部间歇性运动障碍且动脉异常的患者:敏感性34.4%,PPV 96.9%,LR 47.2;(3)除上述最后三个特征外,发病年龄≥70岁的患者:敏感性26.7%,PPV 100%。我们还能确定一个动脉炎风险非常低的亚组,由年龄<70岁、无头痛且颞动脉临床正常的患者组成:敏感性1.1%,PPV 1.7%,LR 0.03。在C组或测试集中,这四个预测模型分别正确识别出57.3%、29.2%、23.6%和3.4%的患者。

结论

在风湿性多肌痛中识别GCA可能性非常高的亚组是可行的。尽管在其中一些亚组中动脉炎的诊断几乎可以确定,但我们建议即便如此仍应通过颞动脉活检来证实。相比之下,对于年龄<70岁且无巨细胞动脉炎颅部特征的风湿性多肌痛患者,血管炎风险非常低,以至于最初可以避免活检,患者可接受小剂量皮质类固醇治疗。

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