Suppr超能文献

机械通气患者气道分泌物重量的指标。

Indicators of Airway Secretion Weight in Mechanically Ventilated Subjects.

机构信息

Physiotherapy Department, St Vincent's Hospital, Sydney, Australia.

Physiotherapy Department, Hampshire Hospitals NHS Foundation Trust, Basingstoke, and North Hampshire Hospital, Hampshire, United Kingdom.

出版信息

Respir Care. 2019 Nov;64(11):1377-1386. doi: 10.4187/respcare.06437. Epub 2019 May 7.

Abstract

BACKGROUND

Clinicians may use adventitious breath sounds on lung auscultation and a "sawtooth" pattern on the ventilator expiratory flow waveform as indicators of the need for chest physiotherapy for airway-secretion clearance in mechanically ventilated patients. This study seeks to identify potential clinical and novel indicators of the weight of airway secretions cleared from a single session of chest physiotherapy in mechanically ventilated subjects.

METHODS

We recorded airway crackles using artificial airway acoustic sound monitoring and computerized lung-sound amplitude using artificial airway acoustic sound detection and compared them to standard clinical assessments in 71 mechanically ventilated subjects immediately prior to a single session of chest physiotherapy. Correlational analyses were undertaken between the weight of airway secretions obtained after the single session of chest physiotherapy as the dependent variable and novel assessments, clinical assessments, patient characteristics, and ventilator parameters as the independent variables. Multiple linear regression analyses were then used to determine the best model to predict the weight of airway secretions obtained from the single chest physiotherapy session. Data are reported as mean and median as appropriate. Significance was set at < .05.

RESULTS

71 mechanically ventilated subjects were included for analysis. Statistically significant associations with the weight of airway secretions included the presence of a sawtooth waveform on expiration and the novel assessment of average airway crackles during inspiration. The best predictive model of the weight of airway secretions included the presence of the sawtooth waveform on expiration and ventilator tidal volume.

CONCLUSIONS

Simple clinical assessments used in this study were able to independently predict the weight of airway secretions cleared during a single session of chest physiotherapy. The novel assessments used in this investigation did not add any further value.

摘要

背景

临床医生可能会根据肺部听诊时出现的意外呼吸音和呼吸机呼气流量波形上的“锯齿”模式,来判断机械通气患者是否需要进行胸部物理治疗以清除气道分泌物。本研究旨在确定机械通气患者单次胸部物理治疗清除气道分泌物量的潜在临床和新型指标。

方法

我们使用人工气道声学声音监测记录气道爆裂音,并使用人工气道声学声音检测计算机化肺音幅度,并在 71 名接受机械通气的患者进行单次胸部物理治疗前,将其与标准临床评估进行比较。在单一次数的胸部物理治疗后,作为因变量,将气道分泌物的重量与新型评估、临床评估、患者特征和呼吸机参数作为自变量进行相关性分析。然后使用多元线性回归分析来确定最佳模型,以预测单一次数的胸部物理治疗中获得的气道分泌物的重量。数据以平均值和中位数报告。显著性水平设定为 <.05。

结果

共纳入 71 名接受机械通气的患者进行分析。与气道分泌物重量有统计学显著关联的因素包括呼气时出现锯齿波形态和吸气时气道爆裂音的新型评估。气道分泌物重量的最佳预测模型包括呼气时出现锯齿波形态和呼吸机潮气量。

结论

本研究中使用的简单临床评估能够独立预测单次胸部物理治疗中清除的气道分泌物量。本研究中使用的新型评估没有增加任何额外的价值。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验