...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Allergy >A Model for the Determination of Pollen Count Using Google Search Queries for Patients Suffering from Allergic Rhinitis
【24h】

A Model for the Determination of Pollen Count Using Google Search Queries for Patients Suffering from Allergic Rhinitis

机译：使用Google搜索查询确定过敏性鼻炎患者花粉数量的模型

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background. The transregional increase in pollen-associated allergies and their diversity have been scientifically proven. However, patchy pollen count measurement in many regions is a worldwide problem with few exceptions. Methods. This paper used data gathered from pollen count stations in Germany, Google queries using relevant allergological/biological keywords, and patient data from three German study centres collected in a prospective, double-blind, randomised, placebo-controlled, multicentre immunotherapy study to analyse a possible correlation between these data pools. Results. Overall, correlations between the patient-based, combined symptom medication score and Google data were stronger than those with the regionally measured pollen count data. The correlation of the Google data was especially strong in the groups of severe allergy sufferers. The results of the three-centre analyses show moderate to strong correlations with the Google keywords (up to 0.8 cross-correlation coefficient, ) in 10 out of 11 groups (three averaged patient cohorts and eight subgroups of severe allergy sufferers high IgE class, high combined symptom medication score, and asthma). Conclusion. For countries with a good Internet infrastructure but no dense network of pollen traps, this could represent an alternative for determining pollen levels and, forecasting the pollen count for the next day.
机译：背景。与花粉有关的过敏及其多样性的跨区域增长已得到科学证明。但是，除了少数例外，许多地区的花粉斑点计数测量是一个世界性的问题。方法。本文使用从德国花粉计数站收集的数据，使用相关变应性/生物学关键字的Google查询以及在前瞻性，双盲，随机，安慰剂对照，多中心免疫疗法研究中收集的来自三个德国研究中心的患者数据来分析这些数据池之间可能的相关性。结果。总体而言，以患者为基础的综合症状药物评分与Google数据之间的相关性强于采用区域测量的花粉计数数据的相关性。在严重的过敏症患者中，Google数据的相关性特别强。三中心分析的结果显示，在11个组中，有10个组（三个平均患者队列和8个IgE级高危重症患者的8个亚组）中有10个与Google关键字具有中等至强的相关性（互相关系数高达> 0.8），合并症状药物得分较高和哮喘）。结论。对于互联网基础设施良好但花粉陷阱网络不密集的国家，这可能是确定花粉水平并预测第二天花粉数量的一种选择。

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