在患有神经肌肉疾病的患者中,基于声音的咳峰值流量估计
Bernat Bertran Recasens1, Ana Balañá Corberó2, Juana María Martínez Llorens2,3,4,5
1ALS/Motor Neuron Diseases Unit, Neurology Department, Hospital del Mar, Barcelona, Spain.
Muscle & nerve
|October 20, 2023
概括
一个智能手机应用程序可靠地估计咳峰值流量 (CPF) 在神经肌肉疾病患者使用咳声音. 这为监测呼吸功能提供了一种方便的方法,即使有面部或面部软弱.
科学领域:
- 神经学 神经学
- 肺部病理学 肺部病理学
- 生物医学工程 生物医学工程
背景情况:
- 咳障碍在神经肌肉疾病中普遍存在,增加呼吸道感染和死亡的风险.
- 目前评估咳强度的方法,如咳峰值流量 (CPF) 计,是复杂的,需要训练有素的人员.
- 需要可靠,易于使用的工具来监测这些患者的呼吸功能.
研究的目的:
- 为了评估智能手机应用程序从咳声音中估计CPF的可靠性.
- 为了确定该应用程序在患有神经肌肉疾病的个体中是否有效,包括那些有面部或面部软弱的人.
主要方法:
- 五十名患有神经肌肉疾病 (ALS,遗传性肌肉病,严重肌) 的患者参与了这项研究.
- 使用标准流量计和智能手机应用程序分析咳声音来测量咳峰值流量 (CPF).
- 使用270L/分钟以下的CPF值来定义异常咳强度.
主要成果:
- 智能手机应用程序显示出强大的可靠性,与流量计相比,其类内相关系数 (ICC) 为0.774 (p < .001).
- 即使在患有口腔面部软弱的患者中也观察到高精度 (ICC = 0.806,p < .001).
- 该应用程序在检测异常CPF (<270 L/min) 中显示了94.4%的灵敏度和100%的特异性.
结论:
- 基于智能手机的咳声音分析提供了神经肌肉疾病患者CPF的可靠估计.
- 这项技术提供了一种方便和可访问的方法来监测呼吸道参与.
- 建议对更大,更多样化的队列进行进一步的研究,以验证这些发现.
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