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呼吸变异度:对麻醉学和重症监护的意义。

Breathing variability-implications for anaesthesiology and intensive care.

机构信息

Departments of Anesthesiology and Intensive Care, Amsterdam UMC, VUMC, ZH 6F 003, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.

出版信息

Crit Care. 2021 Aug 5;25(1):280. doi: 10.1186/s13054-021-03716-0.

DOI:10.1186/s13054-021-03716-0
PMID:34353348
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8339683/
Abstract

The respiratory system reacts instantaneously to intrinsic and extrinsic inputs. This adaptability results in significant fluctuations in breathing parameters, such as respiratory rate, tidal volume, and inspiratory flow profiles. Breathing variability is influenced by several conditions, including sleep, various pulmonary diseases, hypoxia, and anxiety disorders. Recent studies have suggested that weaning failure during mechanical ventilation may be predicted by low respiratory variability. This review describes methods for quantifying breathing variability, summarises the conditions and comorbidities that affect breathing variability, and discusses the potential implications of breathing variability for anaesthesia and intensive care.

摘要

呼吸系统对内在和外在的输入会立即做出反应。这种适应性导致呼吸参数(如呼吸频率、潮气量和吸气流量曲线)发生显著波动。呼吸变异性受到多种情况的影响,包括睡眠、各种肺部疾病、缺氧和焦虑障碍。最近的研究表明,机械通气期间脱机失败可能可以通过低呼吸变异性来预测。本文综述了用于量化呼吸变异性的方法,总结了影响呼吸变异性的条件和合并症,并讨论了呼吸变异性对麻醉和重症监护的潜在影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/162d/8340515/6b66fe32a28f/13054_2021_3716_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/162d/8340515/6b66fe32a28f/13054_2021_3716_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/162d/8340515/6b66fe32a28f/13054_2021_3716_Fig1_HTML.jpg

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本文引用的文献

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J Clin Monit Comput. 2021 Aug;35(4):787-796. doi: 10.1007/s10877-020-00538-3. Epub 2020 Jun 1.
2
Realistically Integrating Machine Learning Into Clinical Practice: A Road Map of Opportunities, Challenges, and a Potential Future.将机器学习切实融入临床实践:机遇、挑战与潜在未来的路线图
Anesth Analg. 2020 May;130(5):1115-1118. doi: 10.1213/ANE.0000000000004575.
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Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.
神经调节通气辅助应用于有肥胖和无肥胖的重症患者:一项前瞻性随机交叉研究。
Ann Intensive Care. 2025 Aug 29;15(1):128. doi: 10.1186/s13613-025-01552-x.
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Wearable Device-Based Respiratory Complexity Analysis for Detecting Pulmonary Congestion in Patients With Heart Failure: Observational Exploratory Study.基于可穿戴设备的呼吸复杂性分析用于检测心力衰竭患者的肺充血:观察性探索性研究
J Med Internet Res. 2025 Aug 27;27:e73488. doi: 10.2196/73488.
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