Monitoring lung recruitment.

IF 3.5 3区 医学 Q1 CRITICAL CARE MEDICINE Current Opinion in Critical Care Pub Date : 2024-06-01 Epub Date: 2024-03-27 DOI:10.1097/MCC.0000000000001157
Gianmaria Cammarota, Rosanna Vaschetto, Luigi Vetrugno, Salvatore M Maggiore
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Abstract

Purpose of review: This review explores lung recruitment monitoring, covering techniques, challenges, and future perspectives.

Recent findings: Various methodologies, including respiratory system mechanics evaluation, arterial bold gases (ABGs) analysis, lung imaging, and esophageal pressure (Pes) measurement are employed to assess lung recruitment. In support to ABGs analysis, the assessment of respiratory mechanics with hysteresis and recruitment-to-inflation ratio has the potential to evaluate lung recruitment and enhance mechanical ventilation setting. Lung imaging tools, such as computed tomography scanning, lung ultrasound, and electrical impedance tomography (EIT) confirm their utility in following lung recruitment with the advantage of radiation-free and repeatable application at the bedside for sonography and EIT. Pes enables the assessment of dorsal lung tendency to collapse through end-expiratory transpulmonary pressure. Despite their value, these methodologies may require an elevated expertise in their application and data interpretation. However, the information obtained by these methods may be conveyed to build machine learning and artificial intelligence algorithms aimed at improving the clinical decision-making process.

Summary: Monitoring lung recruitment is a crucial component of managing patients with severe lung conditions, within the framework of a personalized ventilatory strategy. Although challenges persist, emerging technologies offer promise for a personalized approach to care in the future.

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监测肺招募。
综述的目的:本综述探讨肺募集监测,涵盖技术、挑战和未来展望:各种方法,包括呼吸系统力学评估、动脉血气(ABGs)分析、肺部成像和食管压力(Pes)测量,都被用来评估肺募集情况。作为对 ABGs 分析的支持,利用滞后和募集与充气比对呼吸力学进行评估有可能评估肺募集情况并改善机械通气设置。肺部成像工具,如计算机断层扫描、肺部超声波和电阻抗断层扫描(EIT)证实了它们在跟踪肺部募集方面的实用性,而且超声波和电阻抗断层扫描具有无辐射和可在床边重复应用的优点。Pes 可通过呼气末转肺压力评估背侧肺的塌陷趋势。尽管这些方法很有价值,但在应用和数据解读方面可能需要更高的专业知识。然而,通过这些方法获得的信息可用于构建机器学习和人工智能算法,从而改善临床决策过程。摘要:在个性化通气策略框架内,监测肺募集是管理严重肺部疾病患者的重要组成部分。尽管挑战依然存在,但新兴技术为未来的个性化护理方法带来了希望。
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来源期刊
Current Opinion in Critical Care
Current Opinion in Critical Care 医学-危重病医学
CiteScore
5.90
自引率
3.00%
发文量
172
审稿时长
6-12 weeks
期刊介绍: ​​​​​​​​​Current Opinion in Critical Care delivers a broad-based perspective on the most recent and most exciting developments in critical care from across the world. Published bimonthly and featuring thirteen key topics – including the respiratory system, neuroscience, trauma and infectious diseases – the journal’s renowned team of guest editors ensure a balanced, expert assessment of the recently published literature in each respective field with insightful editorials and on-the-mark invited reviews.
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