DOI: 10.1097/aln.0000000000006332 ISSN: 0003-3022

Tidal swing of endotracheal tube cuff pressure as a measurement of inspiratory effort and lung stress during pressure support ventilation: a proof-of-concept study

Rui-Zhi Zhang, Shan-Shan Xu, Ming-Yue Miao, Xu An, Yang Liu, Yue-Fu Wang, Hong-Liang Li, Jian-Xin Zhou
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Background:

Esophageal pressure (P es ) is the reference standard for monitoring inspiratory effort and lung stress during assisted ventilation, but its routine application is hindered by the lack of specialized equipment and specific training. We aimed to determine whether endotracheal tube cuff pressure (P CUFF ) could serve as a more accessible surrogate.

Methods:

In this prospective study, P es and P CUFF were simultaneously recorded in 30 orally intubated adult patients undergoing pressure support ventilation. A downward pressure support titration (15 to 5 cmH 2 O) was performed. P CUFF was calibrated using occlusion-induced changes in airway pressure. The correlation between tidal swings of P CUFF and P es was analyzed using a linear mixed-effects model. Agreement between the two parameters was evaluated by Bland-Altman analysis (for repeated measures). Diagnostic performance was analyzed for P CUFF to detect extremes of inspiratory effort, using inspiratory muscle pressure (P mus ) and P mus -time product per minute (PTP mus /min) as references, alongside high transpulmonary driving pressure (∆P L >20 cmH 2 O) and high transpulmonary mechanical power (MP L >12 J/min).

Results:

Across 840 analyzed breaths, P CUFF correlated with P es (marginal R ²=0.772; conditional R²=0.949) with a mean bias (limits-of-agreement) of 0.25 (-5.42–5.92) cmH₂O. For detecting low effort (P mus <5 cmH 2 O or PTP mus /min<50 cmH 2 O·s/min), P CUFF yielded areas under the curves (AUCs) of 0.95 (95% confidence interval: 0.91–0.99) and 0.94 (0.86–1.00), respectively. For identifying high effort (P mus >10 cmH 2 O or PTP mus /min>150 cmH 2 O·s/min), the respective AUCs were 0.93 (0.89–0.97) and 0.82 (0.76–0.88). Utilizing a leave-one-out cross-validation framework to prevent overfitting, P CUFF successfully discriminated high ∆P L and MP L with AUCs of 0.89 (0.83–0.95) and 0.88 (0.82–0.93), respectively.

Conclusions:

Although P CUFF cannot entirely replace P es for precise quantification due to relatively wide limits of agreement, it exhibits excellent diagnostic discrimination. P CUFF holds promise as an accessible, continuous bedside monitor for identifying patients with potentially injurious levels of effort, stress and energy intensity.

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