• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

华北地区一家儿童医院中四种评分系统对川崎病患儿静脉注射免疫球蛋白抵抗的预测效能

Efficacy of Four Scoring Systems in Predicting Intravenous Immunoglobulin Resistance in Children with Kawasaki Disease in a Children's Hospital in Beijing, North China.

作者信息

Song Ruixia, Yao Wei, Li Xiaohui

机构信息

Department of Cardiovascular Diseases, Children's Hospital Affiliated to Capital Institute of Pediatrics, Beijing, China.

Capital Institute of Pediatrics, Graduate School of Peking Union Medical College, Beijing, China.

出版信息

J Pediatr. 2017 May;184:120-124. doi: 10.1016/j.jpeds.2016.12.018. Epub 2016 Dec 30.

DOI:10.1016/j.jpeds.2016.12.018
PMID:28043682
Abstract

OBJECTIVE

To evaluate the predictive efficacies of 4 existing scoring systems for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) in hospitalized children with KD in a children's hospital affiliated with the Capital Institute of Pediatrics, Beijing, China.

STUDY DESIGN

We retrospectively analyzed 1569 children with KD treated at our children's hospital between January 2010 and December 2015. Age, sex, clinical manifestations, and pretreatment hematologic indicators were recorded. Scores were assigned using 4 existing scoring systems: Egami, Kobayashi, San Diego, and Formosa. A 4-case table test was used to determine prediction efficacies.

RESULTS

There were 63 IVIG-resistant cases (41 males, 22 females; average age, 2.5 years). Nine cases were classified as high risk for IVIG resistance by the Egami system, and this system had a sensitivity of 14% and a specificity of 86%. Ten cases had Kobayashi high-risk scores, and this system had a sensitivity of 16% and a specificity of 85%. The San Diego system assigned 60 cases as high-risk, and had a sensitivity of 95% and specificity of 3%. Finally, 27 cases had Formosa scores in the high-risk category, and this system had a sensitivity of 43% and a specificity of 47%.

CONCLUSIONS

None of the evaluated systems for assessing the risk for IVIG resistance displayed the combination of sensitivity and specificity necessary for screening. Our analyses show that the 4 scoring systems have limited utility in predicting IVIG resistance among patients with KD in our population.

摘要

目的

在中国北京首都儿科研究所附属儿童医院,评估4种现有评分系统对住院川崎病(KD)患儿静脉注射免疫球蛋白(IVIG)抵抗的预测效能。

研究设计

我们回顾性分析了2010年1月至2015年12月在我院接受治疗的1569例KD患儿。记录其年龄、性别、临床表现及预处理血液学指标。使用4种现有评分系统进行评分:江见、小林、圣地亚哥和福尔摩沙。采用四格表检验确定预测效能。

结果

有63例IVIG抵抗病例(男41例,女22例;平均年龄2.5岁)。江见系统将9例归类为IVIG抵抗高危,该系统敏感性为14%,特异性为86%。小林系统有10例高危评分,该系统敏感性为16%,特异性为85%。圣地亚哥系统将60例归为高危,敏感性为95%,特异性为3%。最后,福尔摩沙系统有27例高危评分,该系统敏感性为43%,特异性为47%。

结论

所评估的IVIG抵抗风险评估系统均未显示出筛查所需的敏感性和特异性的组合。我们的分析表明,这4种评分系统在预测我们研究人群中KD患者的IVIG抵抗方面效用有限。

相似文献

1
Efficacy of Four Scoring Systems in Predicting Intravenous Immunoglobulin Resistance in Children with Kawasaki Disease in a Children's Hospital in Beijing, North China.华北地区一家儿童医院中四种评分系统对川崎病患儿静脉注射免疫球蛋白抵抗的预测效能
J Pediatr. 2017 May;184:120-124. doi: 10.1016/j.jpeds.2016.12.018. Epub 2016 Dec 30.
2
A comparison of efficacy of six prediction models for intravenous immunoglobulin resistance in Kawasaki disease.六种川崎病静脉注射免疫球蛋白抵抗预测模型疗效比较。
Ital J Pediatr. 2018 Mar 9;44(1):33. doi: 10.1186/s13052-018-0475-z.
3
Evaluating the performance of egami, kobayashi and sano scores in predicting IVIG resistance in infant kawasaki disease.评估 egami、小林和佐野评分在预测婴儿川崎病 IVIG 抵抗中的表现。
BMC Pediatr. 2024 Sep 28;24(1):606. doi: 10.1186/s12887-024-05035-z.
4
Comparison of risk scores for predicting intravenous immunoglobulin resistance in Taiwanese patients with Kawasaki disease.比较风险评分预测台湾川崎病患者静脉注射免疫球蛋白耐药的效果。
J Formos Med Assoc. 2021 Oct;120(10):1884-1889. doi: 10.1016/j.jfma.2020.12.010. Epub 2020 Dec 23.
5
Inability of Asian risk scoring systems to predict intravenous immunoglobulin resistance and coronary lesions in Kawasaki disease in an Italian cohort.亚洲风险评分系统无法预测意大利队列川崎病患者静脉注射免疫球蛋白耐药和冠状动脉病变。
Eur J Pediatr. 2019 Mar;178(3):315-322. doi: 10.1007/s00431-018-3297-5. Epub 2018 Nov 29.
6
Predictive tool for intravenous immunoglobulin resistance of Kawasaki disease in Beijing.预测北京川崎病静脉注射免疫球蛋白抵抗的工具。
Arch Dis Child. 2019 Mar;104(3):262-267. doi: 10.1136/archdischild-2017-314512. Epub 2018 Jul 19.
7
Prediction of intravenous immunoglobulin resistance in Kawasaki disease in an East China population.华东地区川崎病患者静脉注射免疫球蛋白耐药性的预测
Clin Rheumatol. 2016 Nov;35(11):2771-2776. doi: 10.1007/s10067-016-3370-2. Epub 2016 Aug 5.
8
A novel scoring system based on sIL-2R for predicting IVIG resistance in Chinese children with KD.基于 sIL-2R 的新型评分系统预测中国 KD 患儿 IVIG 抵抗。
Pediatr Rheumatol Online J. 2024 Aug 18;22(1):76. doi: 10.1186/s12969-024-01015-w.
9
Japanese Kawasaki Disease Scoring Systems: Are they Applicable to the Iranian Population?日本川崎病评分系统:它们适用于伊朗人群吗?
Arch Iran Med. 2020 Jan 1;23(1):31-36.
10
Verification of risk scores to predict i.v. immunoglobulin resistance in incomplete Kawasaki disease.验证预测不完全川崎病静脉注射免疫球蛋白抵抗的风险评分
Pediatr Int. 2016 Feb;58(2):146-51. doi: 10.1111/ped.12755. Epub 2015 Dec 3.

引用本文的文献

1
Explainable deep learning algorithm for distinguishing IVIG-Resistant Kawasaki disease in Shandong peninsula, China.用于鉴别中国山东半岛IVIG无反应性川崎病的可解释深度学习算法
BMC Pediatr. 2025 Aug 28;25(1):658. doi: 10.1186/s12887-025-06082-w.
2
A visualized nomogram to predict intravenous immunoglobulin resistance in Kawasaki disease: a study based on the population in Southern China.预测川崎病静脉注射免疫球蛋白抵抗的可视化列线图:一项基于中国南方人群的研究
Ital J Pediatr. 2025 Apr 12;51(1):117. doi: 10.1186/s13052-025-01964-2.
3
A novel scoring system based on sIL-2R for predicting IVIG resistance in Chinese children with KD.
基于 sIL-2R 的新型评分系统预测中国 KD 患儿 IVIG 抵抗。
Pediatr Rheumatol Online J. 2024 Aug 18;22(1):76. doi: 10.1186/s12969-024-01015-w.
4
Construction and validation of predictive models for intravenous immunoglobulin-resistant Kawasaki disease using an interpretable machine learning approach.使用可解释机器学习方法构建和验证静脉注射免疫球蛋白抵抗性川崎病的预测模型
Clin Exp Pediatr. 2024 Aug;67(8):405-414. doi: 10.3345/cep.2024.00549. Epub 2024 Jul 23.
5
Combination of S100A12/TLR2 signaling molecules and clinical indicators in a new predictive model for IVIG-resistant Kawasaki disease.S100A12/TLR2 信号分子与临床指标联合构建 IVIG 抵抗川崎病的预测新模型。
Sci Rep. 2024 Mar 27;14(1):7261. doi: 10.1038/s41598-024-57897-z.
6
A novel model for predicting intravenous immunoglobulin-resistance in Kawasaki disease: a large cohort study.一种预测川崎病静脉注射免疫球蛋白抵抗的新模型:一项大型队列研究。
Front Cardiovasc Med. 2023 Jul 28;10:1226592. doi: 10.3389/fcvm.2023.1226592. eCollection 2023.
7
Evaluation of Formosa score and diagnostic sensitivity and specificity of four Asian risk scores for predicting intravenous immunoglobulin resistance in Kawasaki disease: a bivariate meta-analysis.福尔摩沙评分及四种亚洲风险评分对川崎病静脉注射免疫球蛋白抵抗预测的诊断敏感性和特异性评估:双变量荟萃分析
Front Cardiovasc Med. 2023 Jun 12;10:1164530. doi: 10.3389/fcvm.2023.1164530. eCollection 2023.
8
Novel Score to Predict Immunoglobulin Resistance in Kawasaki Disease.新型评分预测川崎病的免疫球蛋白抵抗。
Pediatr Cardiol. 2023 Oct;44(7):1546-1551. doi: 10.1007/s00246-023-03175-0. Epub 2023 May 12.
9
Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST.川崎病静脉注射免疫球蛋白抵抗风险预测模型:使用 PROBAST 进行风险评估。
Pediatr Res. 2023 Sep;94(3):1125-1135. doi: 10.1038/s41390-023-02558-6. Epub 2023 Mar 24.
10
Predicting immunoglobulin resistance in Kawasaki disease: an assessment of neutrophil to lymphocyte platelet ratio.预测川崎病的免疫球蛋白抵抗:中性粒细胞与淋巴细胞血小板比值的评估。
Ital J Pediatr. 2022 Dec 30;48(1):208. doi: 10.1186/s13052-022-01400-9.