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呼气分析:在幼儿中进行结核病的有希望的分拣测试
Else M Bijker1, Jonathan P Smith2, Walter Mchembere3
1Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK; Department of Paediatrics, Maastricht University Medical Centre, MosaKids Children's Hospital, Maastricht, the Netherlands.
Tuberculosis (Edinburgh, Scotland)
|September 27, 2024
概括
在婴儿中诊断儿童结核病是具有挑战性的. 新的呼吸分析技术显示出作为儿童结核病查工具的潜力,有助于在幼儿中早期检测.
科学领域:
- 儿科肺病学 儿科肺病学
- 传染病诊断 传染病诊断 传染病诊断
- 发现生物标志物的发现.
背景情况:
- 诊断儿科肺结核,特别是在未吐的婴儿中,带来了重大的临床挑战.
- 呼气分析为呼吸道感染诊断提供了一种非侵入性方法,但其在儿科结核病中的应用需要进一步调查.
- 关于呼吸检测在5岁以下儿童肺结核诊断中的有效性数据有限.
研究的目的:
- 通过使用一种新型设备在怀疑肺结核的五岁以下儿童中评估呼气分析的诊断准确性.
- 评估呼吸分析作为儿童结核病分类工具在资源有限的环境中的潜力.
主要方法:
- 在肯尼亚进行了一项前性横截面研究,涉及118名患有结核病症状的5岁以下儿童.
- 使用便携式电池驱动设备收集出口气样.
- 机器学习算法被用来分析呼吸样本,将其分类为微生物学确认的结核病 (阳性) 或不太可能的结核病 (阴性).
主要成果:
- 最优的机器学习模型实现了0.73.7的曲线下的面积 (AUC).
- 该测试显示灵敏度为86% (95% CI 62-96%) 和特异性为42% (95% CI 30-55%).
- 虽然有希望,但性能指标没有达到世界卫生组织针对结核病诊断的目标产品概况.
结论:
- 呼气分析与机器学习相结合,显示出作为儿科结核病的非侵入性查或分类测试的潜力.
- 进一步的研究和技术改进是必要的,以提高特异性,并满足广泛临床采用的确定的诊目标.
- 这种方法可以促进早期发现和管理幼儿结核病,特别是在诊断基础设施有限的环境中.
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