Prediction of intravenous immunoglobulin unresponsiveness in patients with Kawasaki disease
Prediction of intravenous immunoglobulin unresponsiveness in patients with Kawasaki disease
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DOI：
10.1161/circulationaha.105.592865
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发表时间：
2006-06-06
期刊：
影响因子：
37.8
通讯作者：
Morikawa, Akihiro
中科院分区：
文献类型：
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作者：
Kobayashi, Tohru;Inoue, Yoshinari;Morikawa, Akihiro
背景 - 在本研究中，我们开发了模型来预测川崎病 (KD) 对静脉注射免疫球蛋白 (IVIG) 的无反应。方法和结果 - 我们回顾了 546 名连续 KD 患者（开发数据集）和 204 名后续 KD 患者（验证数据集）的临床记录。所有患者都接受 IVIG 治疗川崎病。 IVIG 无反应者的定义是发烧持续超过 24 小时或无发热期后与 KD 症状相关的复热。构建了 7 变量 Logistic 模型，包括初始治疗时的患病日期、年龄（以月为单位）、代表中性粒细胞的白细胞百分比、血小板计数以及血清天冬氨酸转氨酶、钠和 C 反应蛋白，该模型为开发和验证数据集生成的接受者操作特征曲线下面积分别为 0.84 和 0.90。使用这两个数据集，7 个变量用于生成一个简单的评分模型，该模型给出的接受者操作特征曲线下面积为 0.85。对于逻辑回归模型中 0.15 或以上的截止值以及简单评分模型中 4 分或以上的截止值，逻辑模型中的敏感性和特异性分别为 86% 和 67%，简单评分模型中的敏感性和特异性分别为 86% 和 68%。 kappa 统计值为 0.67，表明逻辑评分模型和简单评分模型之间具有良好的一致性。结论 - 我们的预测模型在识别 KD 患者中的 IVIG 无反应者方面表现出高敏感性和特异性。
Background - In the present study, we developed models to predict unresponsiveness to intravenous immunoglobulin (IVIG) in Kawasaki disease (KD).Methods and Results - We reviewed clinical records of 546 consecutive KD patients (development dataset) and 204 subsequent KD patients (validation dataset). All received IVIG for treatment of KD. IVIG nonresponders were defined by fever persisting beyond 24 hours or recrudescent fever associated with KD symptoms after an afebrile period. A 7-variable logistic model was constructed, including day of illness at initial treatment, age in months, percentage of white blood cells representing neutrophils, platelet count, and serum aspartate aminotransferase, sodium, and C-reactive protein, which generated an area under the receiver-operating-characteristics curve of 0.84 and 0.90 for the development and validation datasets, respectively. Using both datasets, the 7 variables were used to generate a simple scoring model that gave an area under the receiver-operating-characteristics curve of 0.85. For a cutoff of 0.15 or more in the logistic regression model and 4 points or more in the simple scoring model, sensitivity and specificity were 86% and 67% in the logistic model and 86% and 68% in the simple scoring model. The kappa statistic is 0.67, indicating good agreement between the logistic and simple scoring models.Conclusions - Our predictive models showed high sensitivity and specificity in identifying IVIG nonresponders among KD patients.