Rees S E, Larraza S, Dey N, Spadaro S, Brohus J B, Winding R W, Volta C A, Karbing D S
Respiratory and Critical Care Group (rcare), Department of Health Science and Technology, Aalborg University, Fredrik Bajersvej 7E, 9220, Aalborg Øst, Denmark.
Department of Anaesthesia and Intensive Care, Regions Hospital Herning, Herning, Denmark.
J Clin Monit Comput. 2017 Aug;31(4):773-781. doi: 10.1007/s10877-016-9903-z. Epub 2016 Jun 25.
Incomplete expiration of tidal volume can lead to dynamic hyperinflation and auto-PEEP. Methods are available for assessing these, but are not appropriate for patients with respiratory muscle activity, as occurs in pressure support. Information may exist in expiratory flow and carbon dioxide measurements, which, when taken together, may help characterize dynamic hyperinflation. This paper postulates such patterns and investigates whether these can be seen systematically in data. Two variables are proposed summarizing the number of incomplete expirations quantified as a lack of return to zero flow in expiration (IncExp), and the end tidal CO variability (varETCO), over 20 breaths. Using these variables, three patterns of ventilation are postulated: (a) few incomplete expirations (IncExp < 2) and small varETCO; (b) a variable number of incomplete expirations (2 ≤ IncExp ≤ 18) and large varETCO; and (c) a large number of incomplete expirations (IncExp > 18) and small varETCO. IncExp and varETCO were calculated from data describing respiratory flow and CO signals in 11 patients mechanically ventilated at 5 levels of pressure support. Data analysis showed that the three patterns presented systematically in the data, with periods of IncExp < 2 or IncExp > 18 having significantly lower variability in end-tidal CO than periods with 2 ≤ IncExp ≤ 18 (p < 0.05). It was also shown that sudden change in IncExp from either IncExp < 2 or IncExp > 18 to 2 ≤ IncExp ≤ 18 results in significant, rapid, change in the variability of end-tidal CO p < 0.05. This study illustrates that systematic patterns of expiratory flow and end-tidal CO are present in patients in supported mechanical ventilation, and that changes between these patterns can be identified. Further studies are required to see if these patterns characterize dynamic hyperinflation. If so, then their combination may provide a useful addition to understanding the patient at the bedside.
潮气量呼气不完全可导致动态肺过度充气和内源性呼气末正压。有多种方法可用于评估这些情况,但对于存在呼吸肌活动的患者并不适用,比如在压力支持通气时就会出现这种情况。呼气流量和二氧化碳测量中可能存在相关信息,综合这些信息或许有助于描述动态肺过度充气。本文提出了这样的模式,并研究这些模式是否能在数据中系统地显现出来。提出了两个变量来总结20次呼吸中不完全呼气的次数(量化为呼气时流量未恢复到零,即IncExp)以及呼气末二氧化碳变异性(varETCO)。利用这些变量,假定了三种通气模式:(a) 少量不完全呼气(IncExp < 2)且varETCO较小;(b) 不完全呼气次数可变(2 ≤ IncExp ≤ 18)且varETCO较大;(c) 大量不完全呼气(IncExp > 18)且varETCO较小。IncExp和varETCO是根据11例接受5种压力支持水平机械通气患者的呼吸流量和二氧化碳信号数据计算得出的。数据分析表明,这三种模式在数据中系统地呈现出来,IncExp < 2或IncExp > 18的时间段内呼气末二氧化碳的变异性显著低于2 ≤ IncExp ≤ 18的时间段(p < 0.05)。研究还表明,IncExp从IncExp < 2或IncExp > 18突然转变为2 ≤ IncExp ≤ 18会导致呼气末二氧化碳变异性显著、快速变化(p < 0.05)。本研究表明,接受机械通气支持的患者存在呼气流量和呼气末二氧化碳的系统模式,并且可以识别这些模式之间的变化。需要进一步研究以确定这些模式是否可表征动态肺过度充气。如果是这样,那么它们的组合可能会为床边了解患者情况提供有益补充。