Kobayashi Tohru, Inoue Yoshinari, Takeuchi Kazuo, Okada Yasunori, Tamura Kazushi, Tomomasa Takeshi, Kobayashi Tomio, Morikawa Akihiro
Department of Pediatrics and Developmental Medicine, Gunma University Graduate School of Medicine, Gunma 377-8511, Japan.
Circulation. 2006 Jun 6;113(22):2606-12. doi: 10.1161/CIRCULATIONAHA.105.592865. Epub 2006 May 30.
In the present study, we developed models to predict unresponsiveness to intravenous immunoglobulin (IVIG) in Kawasaki disease (KD).
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.
Our predictive models showed high sensitivity and specificity in identifying IVIG nonresponders among KD patients.
在本研究中，我们开发了模型来预测川崎病（KD）患者对静脉注射免疫球蛋白（IVIG）无反应。
我们回顾了546例连续的KD患者（开发数据集）和204例后续KD患者（验证数据集）的临床记录。所有患者均接受IVIG治疗KD。IVIG无反应者定义为发热持续超过24小时或在无热期后出现与KD症状相关的再发发热。构建了一个包含初始治疗时的病程天数、月龄、代表中性粒细胞的白细胞百分比、血小板计数、血清天冬氨酸转氨酶、钠和C反应蛋白的7变量逻辑模型，该模型在开发数据集和验证数据集上的受试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，这7个变量被用于生成一个简单评分模型，其受试者操作特征曲线下面积为0.85。对于逻辑回归模型中截断值为0.15或更高以及简单评分模型中截断值为4分或更高的情况，逻辑模型的敏感性和特异性分别为86%和67%，简单评分模型的敏感性和特异性分别为86%和68%。kappa统计量为0.67，表明逻辑模型和简单评分模型之间具有良好的一致性。
我们的预测模型在识别KD患者中的IVIG无反应者方面显示出高敏感性和特异性。
