Fava de Lima Felipe, Siqueira de Nóbrega Raquel, Cesare Biselli Paolo José, Takachi Moriya Henrique
Biomedical Engineering Laboratory, Escola Politécnica, University of São Paulo (USP), São Paulo, Brazil.
Intensive Care Unit, University Hospital of University of São Paulo (USP), São Paulo, Brazil.
J Clin Monit Comput. 2024 Oct;38(5):961-979. doi: 10.1007/s10877-024-01171-0. Epub 2024 Jul 1.
This pilot study aimed to investigate the relation between cardio-respiratory parameters derived from Central Venous Pressure (CVP) waveform and Extubation Failure (EF) in mechanically ventilated ICU patients during post-extubation period. This study also proposes a new methodology for analysing these parameters during rest/sleep periods to try to improve the identification of EF. We conducted a prospective observational study, computing CVP-derived parameters including breathing effort, spectral analyses, and entropy in twenty critically ill patients post-extubation. The Dynamic Warping Index (DWi) was calculated from the respiratory component extracted from the CVP signal to identify rest/sleep states. The obtained parameters from EF patients and patients without EF were compared both during arbitrary periods and during reduced DWi (rest/sleep). We have analysed data from twenty patients of which nine experienced EF. Our findings may suggest significantly increased respiratory effort in EF patients compared to those successfully extubated. Our study also suggests the occurrence of significant change in the frequency dispersion of the cardiac signal component. We also identified a possible improvement in the differentiation between the two groups of patients when assessed during rest/sleep states. Although with caveats regarding the sample size, the results of this pilot study may suggest that CVP-derived cardio-respiratory parameters are valuable for monitoring respiratory failure during post-extubation, which could aid in managing non-invasive interventions and possibly reduce the incidence of EF. Our findings also indicate the possible importance of considering sleep/rest state when assessing cardio-respiratory parameters, which could enhance respiratory failure detection/monitoring.
这项初步研究旨在调查机械通气的重症监护病房(ICU)患者拔管后期间,从中心静脉压(CVP)波形得出的心肺参数与拔管失败(EF)之间的关系。本研究还提出了一种在休息/睡眠期间分析这些参数的新方法,以试图改善对拔管失败的识别。我们进行了一项前瞻性观察研究,计算了20例重症患者拔管后的CVP衍生参数,包括呼吸努力、频谱分析和熵。从CVP信号中提取的呼吸成分计算动态规整指数(DWi),以识别休息/睡眠状态。在任意时间段以及DWi降低(休息/睡眠)期间,对拔管失败患者和未发生拔管失败患者获得的参数进行了比较。我们分析了20例患者的数据,其中9例经历了拔管失败。我们的研究结果可能表明,与成功拔管的患者相比,拔管失败患者的呼吸努力显著增加。我们的研究还表明,心脏信号成分的频率离散发生了显著变化。我们还发现,在休息/睡眠状态下评估时,两组患者之间的差异可能有所改善。尽管样本量存在一定限制,但这项初步研究的结果可能表明,CVP衍生的心肺参数对于监测拔管后期间的呼吸衰竭很有价值,这有助于管理无创干预措施,并可能降低拔管失败的发生率。我们的研究结果还表明,在评估心肺参数时考虑睡眠/休息状态可能具有重要意义,这可以增强呼吸衰竭的检测/监测。