Prediction of high airway pressure using a non-linear autoregressive model of pulmonary mechanics

Abstract

BackgroundFor mechanically ventilated patients with acute respiratory distress syndrome (ARDS), suboptimal PEEP levels can cause ventilator induced lung injury (VILI). In particular, high PEEP and high peak inspiratory pressures (PIP) can cause over distension of alveoli that is associated with VILI. However, PEEP must also be sufficient to maintain recruitment in ARDS lungs. A lung model that accurately and precisely predicts the outcome of an increase in PEEP may allow dangerous high PIP to be avoided, and reduce the incidence of VILI.Methods and resultsSixteen pressure-flow data sets were collected from nine mechanically ventilated ARDs patients that underwent one or more recruitment manoeuvres. A nonlinear autoregressive (NARX) model was identified on one or more adjacent PEEP steps, and extrapolated to predict PIP at 2, 4, and 6 cmH2O PEEP horizons. The analysis considered whether the predicted and measured PIP exceeded a threshold of 40 cmH2O. A direct comparison of the method was made using the first order model of pulmonary mechanics (FOM(I)). Additionally, a further, more clinically appropriate method for the FOM was tested, in which the FOM was trained on a single PEEP prior to prediction (FOM(II)). The NARX model exhibited very high sensitivity (> 0.96) in all cases, and a high specificity (> 0.88). While both FOM methods had a high specificity (> 0.96), the sensitivity was much lower, with a mean of 0.68 for FOM(I), and 0.82 for FOM(II).ConclusionsClinically, false negatives are more harmful than false positives, as a high PIP may result in distension and VILI. Thus, the NARX model may be more effective than the FOM in allowing clinicians to reduce the risk of applying a PEEP that results in dangerously high airway pressures.

Virtual patients for mechanical ventilation in the intensive care unit

“…Statistical models efficiently provide best mathematical combinations for predictive relationships, but offer little understanding of the underlying mechanics [24][25][26][27] , even if prediction accuracy is acceptable [ 26 , 27 ]. A mechanical model offers more explicit meaning, physically and physiologically, and is thus more suitable for virtual patient models [25] .…”

Effects of training flights of combat jet pilots on parameters of airway function, diffusing capacity and systemic oxidative stress, and their association with flight parameters

“…These interventions raise the question as to whether the support systems themselves may lead to adverse physiological effects. In intensive care medicine, it is known that increased airway pressures can have detrimental effects on the lung [ 4 , 5 ] causing barotrauma and ventilation-induced lung injury in extreme cases [ 6 , 7 ]. Furthermore, the dry inhaled air may induce irritation of the upper respiratory tract [ 8 ], and the increased partial pressure of oxygen and its variation over time can lead to resorption atelectasis [ 9 ] in the lung periphery, or the formation of oxygen radicals leading to both local, and systemic, oxidative stress and DNA damage [ 10 , 11 ].…”

Effects of training flights of combat jet pilots on parameters of airway function, diffusing capacity and systemic oxidative stress, and their association with flight parameters

“…These interventions raise the question whether the support systems themselves may not without adverse physiological effects. In intensive care medicine, it is known that increased airway pressures can have detrimental effects on the lung [4,5] causing barotrauma and ventilation-induced lung injury in extreme cases [6,7]. Furthermore, the dry inhaled air may induce irritations of the upper respiratory tract [8], and the increased partial pressure of oxygen and its variation over time can lead to resorption atelectasis [9] in the lung periphery, or the formation of oxygen radicals leading to both, local and systemic, oxidative stress and DNA damage [10,11].…”