Novel Predictors of Intravenous Immunoglobulin Resistance in Chinese Children with Kawasaki Disease

医学 川崎病 接收机工作特性 逻辑回归 计分系统 内科学 曲线下面积 动脉
作者
Peipei Fu,Zhong-Dong Du,Yuesong Pan
出处
期刊:Pediatric Infectious Disease Journal [Ovid Technologies (Wolters Kluwer)]
卷期号:32 (8): e319-e323 被引量:64
标识
DOI:10.1097/inf.0b013e31828e887f
摘要

The purpose of this study was to develop a predictive scoring system to identify intravenous immunoglobulin resistance in children with Kawasaki disease, to implement additional therapies early in the course of their illness and prevent coronary artery lesions.We performed a retrospective review of children with Kawasaki disease treated within 10 days of fever onset. To identify independent predictors of intravenous immunoglobulin resistance, multivariable logistic regression models were constructed using variables selected by univariable analysis. The independent predictors were combined into a new scoring system and compared with 2 existing systems. The discriminatory capacity of the scoring system was assessed using the area under the receiver operating characteristic curves.By logistic regression analysis, polymorphous exanthema, changes around the anus, days of illness at initial treatment, percentage of neutrophils, C-reactive protein levels, albumin levels, and total bilirubin proved to be independent predictors of intravenous immunoglobulin resistance. The new scoring system gave an area under the receiver operating characteristic curve of 0.672. In this scoring system, 2 risk strata were identified: low risk, with scores of 0-3, and high risk, with scores of ≥4. The sensitivity was 54.1% and the specificity was 71.2%.The new scoring system had a higher specificity and sensitivity for Chinese children, compared with the Kobayashi scoring system and the Egami scoring system, but, unfortunately, the new scoring system was not good enough to be widely used because of its low sensitivity.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
SciGPT应助pendulum采纳,获得10
刚刚
yanglina062完成签到 ,获得积分10
2秒前
思源应助pakho采纳,获得10
2秒前
3秒前
pendulum完成签到,获得积分10
5秒前
5秒前
科研通AI2S应助Zjin宇采纳,获得10
5秒前
Russia完成签到 ,获得积分10
6秒前
7秒前
8秒前
天真的白柏完成签到,获得积分10
10秒前
逗号就是逗完成签到,获得积分10
10秒前
清脆松发布了新的文献求助20
10秒前
10秒前
菠萝派完成签到,获得积分10
10秒前
11秒前
zyy123888发布了新的文献求助10
12秒前
12秒前
13秒前
sukasuka发布了新的文献求助30
13秒前
14秒前
14秒前
15秒前
轻松曼青完成签到 ,获得积分20
15秒前
lilili发布了新的文献求助10
15秒前
害怕的盼芙完成签到,获得积分10
16秒前
momomi完成签到,获得积分10
16秒前
爱科研的粥粥完成签到,获得积分10
16秒前
17秒前
早早发布了新的文献求助10
18秒前
科目三应助科研小菜狗采纳,获得10
20秒前
20秒前
ZCL发布了新的文献求助30
20秒前
20秒前
cfy发布了新的文献求助10
20秒前
程程完成签到,获得积分10
21秒前
李昕123发布了新的文献求助10
21秒前
zyy123888完成签到,获得积分10
22秒前
BeBop发布了新的文献求助20
26秒前
pakho发布了新的文献求助10
26秒前
高分求助中
Evolution 10000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Distribution Dependent Stochastic Differential Equations 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3158115
求助须知:如何正确求助?哪些是违规求助? 2809457
关于积分的说明 7882079
捐赠科研通 2467936
什么是DOI,文献DOI怎么找? 1313819
科研通“疑难数据库(出版商)”最低求助积分说明 630538
版权声明 601943