Lung Opening and Closing during Ventilation of Acute Respiratory Distress Syndrome

Caironi, Pietro; Cressoni, Massimo; Chiumello, Davide; Ranieri, Marco; Quintel, Michael; Russo, Sebastiano G.; Cornejo, Rodrigo; Bugedo, Guillermo; Carlesso, Eleonora; Russo, R; Caspani, Luisa; Gattinoni, Luciano

doi:10.1164/rccm.200905-0787oc

Cited by 308 publications

(240 citation statements)

References 40 publications

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“…In fact, when adapting the relationship between the duration of mechanical ventilation and the lung strain applied to patients affected by ARDS, it is surprising that even a V T equal to 12 ml/kg body weight leads to a lung strain largely below the threshold of 1.5. In fact, if we consider a man of 70 kg predicted body weight with an FRC of about 900 ml [15], the application of a V T of 12 ml/kg body weight and a PEEP level of 10 cmH 2 O will result in a lung strain of about 1.3, which will even be reduced to 0.70 when corrected for the actual time of application during each tidal breath! Although representing a rough estimate, these data may suggest that the mechanisms by which a low V T ventilation improves survival in ARDS may hardly be explained only by the reduction in an excessive global lung stress and strain.…”

Section: Discussionmentioning

confidence: 99%

“…In ARDS, we have recently shown that both V T expressed in relation to body weight and the airway pressure applied are ''inadequate surrogates'' for the evaluation of the actual lung stress and strain applied, due to a large variability in lung resting volume (functional residual capacity, FRC) and in chest wall mechanics [14]. Moreover, we have recently reported [15] that different mechanisms, such as the intratidal lung opening and closing, may be responsible for the lung injury associated with ventilation in ALI/ARDS, therefore questioning direct translation to humans of findings obtained from experimental settings regarding the role of an excessive V T and airway pressure.…”

Section: Introductionmentioning

confidence: 99%

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Time to generate ventilator-induced lung injury among mammals with healthy lungs: a unifying hypothesis

et al. 2011

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Purpose: To investigate ventilator-induced lung injury (VILI), several experimental models were designed including different mammalian species and ventilator settings, leading to a large variability in the observed time-course and injury severity. We hypothesized that the time-course of VILI may be fully explained from a single perspective when considering the insult actually applied, i.e. lung stress and strain. Methods: Studies in which healthy animals were aggressively ventilated until preterminal VILI were selected via a Medline search. Data on morphometry, ventilator settings, respiratory function and duration of ventilation were derived. For each animal group, lung stress (transpulmonary pressure) and strain (endinspiratory lung inflation/lung resting volume ratio) were estimated. Results: From the Medline search 20 studies including five mammalian species (sheep, pigs, rabbits, rats, mice) were selected. Time to achieve preterminal VILI varied widely (18-2,784 min), did not correlate with either tidal volume (expressed in relation to body weight) or airway pressure applied, but was weakly associated with lung stress (r 2 = 0.25, p = 0.008). In contrast, the duration of mechanical ventilation was closely correlated with both lung strain (r 2 = 0.85, p \ 0.0001) and lung strain weighted for the actual time of application during each breath (r 2 = 0.83, p \ 0.0001), according to exponential decay functions. When it was normalized for the lung strain applied, larger species showed a greater resistance to VILI than smaller species (medians, 25th-75th percentiles: 690, 460-2,001 min vs. 16, 4-59 min, respectively; p \ 0.001). Conclusion: Lung strain may play a critical role as a unifying rule describing the development of VILI among mammals with healthy lungs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time to generate ventilator-induced lung injury among mammals with healthy lungs: a unifying hypothesis

et al. 2011

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“…In addition a recent study showed that high PEEP levels significantly decreased the opening and closing tissue without significantly increasing alveolar inflation only in patients with higher compared to lower lung recruitability [30]. Therefore the knowledge of lung recruitability may impact the mechanical ventilation setting [11].…”

Section: Discussionmentioning

confidence: 99%

“…However, it would be better to set an inappropriately high PEEP in patients with low Fig. 4 Receiver operating characteristic curve for lung recruitability, mean visual anatomical lung CT scan analysis recruitability causing possible lung overdistension and hemodynamic impairment than the risk of not applying high PEEP in patients with high recruitability promoting intratidal collapse which is widely recognized as a damaging factor [11,22,23,30,41].…”

Section: Discussionmentioning

confidence: 99%

Visual anatomical lung CT scan assessment of lung recruitability

et al. 2012

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Purpose: The computation of lung recruitability in acute respiratory distress syndrome (ARDS) is advocated to set positive end-expiratory pressure (PEEP) for preventing lung collapse. The quantitative lung CT scan, obtained by manual image processing, is the reference method but it is time consuming. The aim of this study was to evaluate the accuracy of a visual anatomical analysis compared with a quantitative lung CT scan analysis in assessing lung recruitability. Methods: Fifty sets of two complete lung CT scans of ALI/ARDS patients computing lung recruitment were analyzed. Lung recruitability computed at an airway pressure of 5 and 45 cmH 2 O was defined as the percentage decrease in the collapsed/ consolidated lung parenchyma assessed by two expert radiologists using a visual anatomical analysis and as the decrease in not aerated lung regions using a quantitative analysis computed by dedicated software.Results: Lung recruitability was 11.3 % (interquartile range 7.39-16.41) and 15.5 % (interquartile range 8.18-21.43) with the visual anatomical and quantitative analysis, respectively. In the Bland-Altman analysis, the bias and agreement bands between the visual anatomical and quantitative analysis were -2.9 % (-11.8 to ?5.9 %). The ROC curve showed that the optimal cutoff values for the visual anatomical analysis in predicting high versus low lung recruitability was 8.9 % (area under the ROC curve 0.9248, 95 % CI 0.8550-0.9946). Considering this cutoff, the sensitivity, specificity, and diagnostic accuracy were 0.96, 0.76, and 0.86, respectively. Conclusions: Visual anatomical analysis can classify patients into those with high and low lung recruitability allowing more intensivists to get access to lung recruitability assessment.

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“…The application of adequate levels of PEEP in the management of ARDS patients remains a critical issue for further investigation [11]. A large portion of potentially recruitable lung units seems to be an independent risk factor for mortality in ARDS [12], thus the benefit of reducing tidal recruitment by increasing PEEP levels may prevail over the effect of increasing alveolar over-distension in this subgroup of patients [13]. A reliable tool at bedside to set desirable PEEP and VT is critical [11].…”

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confidence: 99%

Forced oscillation technique: an alternative tool to define the optimal PEEP?

2011

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Lung Opening and Closing during Ventilation of Acute Respiratory Distress Syndrome

Abstract: In ARDS, especially in patients with higher lung recruitability, the beneficial impact of reducing intratidal alveolar opening and closing by increasing PEEP prevails over the effects of increasing alveolar strain.

Cited by 308 publications

References 40 publications

Time to generate ventilator-induced lung injury among mammals with healthy lungs: a unifying hypothesis

Time to generate ventilator-induced lung injury among mammals with healthy lungs: a unifying hypothesis

Visual anatomical lung CT scan assessment of lung recruitability

Forced oscillation technique: an alternative tool to define the optimal PEEP?

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