慢性呼吸道疾病患者的生理信号:一个系统的审查
Nawal Alotaibi1,2, Maggie Cheung3, Amar Shah4,3
1UCL Respiratory, University College London, London, UK n.alotaibi@ucl.ac.uk.
概括
对生理信号的 entropy 分析可以帮助检测慢性呼吸道疾病 (CRD) 恶化,并评估 COPD 和喘中的疾病严重程度. 心率变化和空气流量的低率表明疾病严重程度增加.
科学领域:
- 生理学 生理学 生理学
- 非线性动力学是一种非线性动力学.
- 生物医学工程 生物医学工程
背景情况:
- 慢性呼吸道疾病 (CRD),如COPD和喘,对患者和医疗保健产生重大影响.
- 使用诸如分析之类的非线性测量方法进行持续的生理监测,对CRD诊断和管理有很大的前景.
- 值量化了生理信号的复杂性,反映了控制机制的参与.
研究的目的:
- 系统地审查有关CRD患者生理信号中变化的现有证据.
- 探索用于CRD诊断和监测的分析的潜力.
主要方法:
- 在遵守PRISMA指南的基础上进行系统审查.
- 在Scopus,Medline,CINAHL和Embase数据库中进行的搜索.
- 从11项包括研究的证据进行了定性综合,评估了使用纽卡斯尔-太华尺度的信号,类型和结果.
主要成果:
- 与健康个体相比,COPD和喘患者心率变化 (HRV) 和空气流量缩.
- 在COPD和喘中,随着疾病严重程度的增加,值水平下降.
- 与稳定状态相比,COPD恶化期间外周氧和 (SpO2) 度增加.
结论:
- 对生理信号的 entropy 分析具有 COPD 恶化早期检测的潜力.
- 这种方法可能有助于区分COPD和喘的疾病严重程度.
- 需要进一步的研究,以建立分析作为临床工具,特别是对于其他CRD如支气管切除症和间歇性肺部疾病.
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