Physiological signal entropy in patients with chronic respiratory disease: a systematic review.

IF 9 1区 医学 Q1 RESPIRATORY SYSTEM
European Respiratory Review Pub Date : 2025-04-30 Print Date: 2025-04-01 DOI:10.1183/16000617.0252-2024
Nawal Alotaibi, Maggie Cheung, Amar Shah, John R Hurst, Ali R Mani, Swapna Mandal
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引用次数: 0

Abstract

Background: Chronic respiratory diseases (CRDs) such as COPD and asthma have a substantial impact on patients and healthcare systems. Recent research on diagnosing and monitoring CRDs highlights the potential of continuous measurement of physiological parameters using nonlinear measures such as entropy analysis. Entropy measures the irregularity and complexity of physiological signals, reflecting the engagement of physiological control mechanisms. This systematic review examines the current evidence on changes in the entropy of physiological signals in CRDs.

Methods: The review follows Preferred Reporting in Systematic Reviews and Meta-Analyses (PRISMA) guidelines and includes studies from databases such as Scopus, Medline, CINAHL and Embase. Quality assessment was conducted using the Newcastle-Ottawa Scale. Evidence was qualitatively synthesised, taking into account entropy signals, entropy type and results.

Results: 11 studies met the inclusion criteria. Entropy in signals including heart rate variability (HRV), airflow, peripheral oxygen saturation (S pO2 ), inter-breath interval and tidal volume were evaluated. The findings indicated that patients with COPD and asthma exhibit lower entropy in HRV and airflow compared to healthy controls, with entropy decreasing as disease severity increases. Conversely, S pO2 entropy values were increased during an exacerbation compared to stable COPD.

Conclusion: The review highlights the potential of entropy analysis of physiological signals for early detection of COPD exacerbations and for differentiating between various levels of disease severity in both COPD and asthma. Additionally, it identifies research gaps, particularly in relation to other CRDs such as bronchiectasis and interstitial lung diseases. Further research is needed to facilitate the development of this approach into a fully effective tool for clinical practice.

慢性呼吸系统疾病患者的生理信号熵:系统综述。
背景:慢性呼吸系统疾病(CRDs)如COPD和哮喘对患者和卫生保健系统有重大影响。最近在诊断和监测crd方面的研究强调了使用非线性测量(如熵分析)连续测量生理参数的潜力。熵衡量生理信号的不规则性和复杂性,反映生理控制机制的参与。本系统综述探讨了crd中生理信号熵变化的现有证据。方法:本综述遵循系统评价和荟萃分析(PRISMA)指南中的首选报告,包括来自Scopus、Medline、CINAHL和Embase等数据库的研究。使用纽卡斯尔-渥太华量表进行质量评估。考虑到熵信号、熵类型和结果,对证据进行定性合成。结果:11项研究符合纳入标准。评估心率变异性(HRV)、气流、外周氧饱和度(S pO2)、呼吸间隔期和潮气量等信号的熵。研究结果表明,与健康对照相比,COPD和哮喘患者HRV和气流熵较低,熵随着疾病严重程度的增加而降低。相反,与稳定的COPD相比,S pO2熵值在加重期间增加。结论:该综述强调了生理信号熵分析在COPD急性加重早期检测和区分COPD和哮喘不同疾病严重程度方面的潜力。此外,它还确定了研究空白,特别是与其他慢性疾病,如支气管扩张和间质性肺疾病有关的空白。需要进一步的研究来促进这种方法的发展,使其成为临床实践的有效工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
European Respiratory Review
European Respiratory Review Medicine-Pulmonary and Respiratory Medicine
CiteScore
14.40
自引率
1.30%
发文量
91
审稿时长
24 weeks
期刊介绍: The European Respiratory Review (ERR) is an open-access journal published by the European Respiratory Society (ERS), serving as a vital resource for respiratory professionals by delivering updates on medicine, science, and surgery in the field. ERR features state-of-the-art review articles, editorials, correspondence, and summaries of recent research findings and studies covering a wide range of topics including COPD, asthma, pulmonary hypertension, interstitial lung disease, lung cancer, tuberculosis, and pulmonary infections. Articles are published continuously and compiled into quarterly issues within a single annual volume.
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