• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Clinical and experimental allergy : >Predicting steroid responsiveness in patients with asthma using exhaled breath profiling
【24h】

Predicting steroid responsiveness in patients with asthma using exhaled breath profiling

机译：使用呼出气曲线分析预测哮喘患者的类固醇反应

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background: Exhaled breath contains disease-dependent volatile organic compounds (VOCs), which may serve as biomarkers distinguishing clinical phenotypes in asthma. Their measurement may be particularly beneficial in relation to treatment response. Objective: Our aim was to compare the performance of electronic nose (eNose) breath analysis with previously investigated techniques (sputum eosinophils, exhaled nitric oxide (FeNO) and airway hyperresponsiveness) to discriminate asthma from controls and identify steroid responsiveness in steroid-free patients. Trial registration ACTRN12613000038796. Methods: Twenty-five patients with mild/moderate asthma had their inhaled steroid treatment discontinued until loss of control or 28 days. They were subsequently treated with oral prednisone 30 mg/day for 14 days. Steroid responsiveness was defined as an increase of either 12% FEV1 or 2 doubling doses PC20AMP. Steroid-free assessment of sputum eosinophils, FeNO and exhaled breath VOCs were used to construct algorithms predicting steroid responsiveness. Performance characteristics were compared by ROC analysis. Results: The eNose discriminated between asthma and controls (area under the curve = 0.766 ± 0.14; P = 0.002) with similar accuracy to FeNO (0.862 ± 0.12; P 0.001) and sputum eosinophils (0.814 ± 0.15; P 0.001). Steroid responsiveness was predicted with greater accuracy by VOC-analysis (AUC = 0.883 ± 0.16; P = 0.008) than FeNO (0.545 ± 0.28; P = 0.751) or sputum eosinophils (0.610 ± 0.29; P = 0.441). Conclusions and Clinical Relevance: Breath analysis by eNose can identify asthmatic patients and may be used to predict their response to steroids with greater accuracy than sputum eosinophils or FeNO. This implies a potential role for breath analysis in the tailoring of treatment for asthma patients.
机译：背景：呼气中含有疾病相关的挥发性有机化合物（VOC），可作为区分哮喘临床表型的生物标志物。它们的测量在治疗反应方面可能特别有益。目的：我们的目的是将电子鼻（eNose）呼吸分析与先前研究的技术（痰嗜酸性粒细胞，呼出气一氧化氮（FeNO）和气道高反应性）的性能进行比较，以将哮喘与对照组区别开来，并确定无类固醇患者的类固醇反应性。试用注册ACTRN12613000038796。方法：25例轻度/中度哮喘患者已停止吸入类固醇药物治疗，直至失去控制或28天。他们随后接受口服泼尼松30 mg /天治疗14天。类固醇反应性定义为PC20AMP增加> 12％FEV1或增加2倍。痰中嗜酸性粒细胞，FeNO和呼气VOC的无类固醇评估用于构建预测类固醇反应性的算法。通过ROC分析比较性能特征。结果：eNose区分哮喘和对照组（曲线下面积= 0.766±0.14; P = 0.002），其准确性与FeNO（0.862±0.12; P <0.001）和痰嗜酸性粒细胞（0.814±0.15; P <0.001）相似。通过VOC分析（AUC = 0.883±0.16; P = 0.008）比FeNO（0.545±0.28; P = 0.751）或痰嗜酸性粒细胞（0.610±0.29; P = 0.441）更准确地预测类固醇反应性。结论和临床意义：eNose进行的呼吸分析可以识别哮喘患者，并且可以用来预测他们对类固醇的反应，其准确性要比痰中的嗜酸性粒细胞或FeNO高。这暗示了呼吸分析在哮喘患者的治疗量身定制中的潜在作用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号