Primary blast lung injury simulator: a new computerised model

Haque, Mainul; Das, Anup; Scott, Timothy; Bates, Declan G.; Hardman, Jonathan G.

doi:10.1136/jramc-2018-000989

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…Our PBLI simulator is a high-fidelity iterative computational model of human cardiopulmonary pathophysiology [10]. It can accommodate both mechanical and spontaneous ventilation, evolving acute lung injury including non-cardiogenic pulmonary oedema as well as ventilator-induced lung injury (VILI).…”

Section: Methodsmentioning

confidence: 99%

“…As PBLI is by nature a sporadic disease born out of conflict, randomized controlled clinical trials to investigate alternative management strategies are not feasible-clinical care has been, and will continue to be, guided by surrogate models of the disease. Such models have traditionally been in vivo animal models [5][6][7], but there has recently been increasing interest in the use of in silico models of human PBLI pathophysiology [8][9][10].…”

mentioning

confidence: 99%

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Management of primary blast lung injury: a comparison of airway pressure release versus low tidal volume ventilation

Scott

Das

Haque

et al. 2020

ICMx

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Background Primary blast lung injury (PBLI) presents as a syndrome of respiratory distress and haemoptysis resulting from explosive shock wave exposure and is a frequent cause of mortality and morbidity in both military conflicts and terrorist attacks. The optimal mode of mechanical ventilation for managing PBLI is not currently known, and clinical trials in humans are impossible due to the sporadic and violent nature of the disease. Methods A high-fidelity multi-organ computational simulator of PBLI pathophysiology was configured to replicate data from 14 PBLI casualties from the conflict in Afghanistan. Adaptive and responsive ventilatory protocols implementing low tidal volume (LTV) ventilation and airway pressure release ventilation (APRV) were applied to each simulated patient for 24 h, allowing direct quantitative comparison of their effects on gas exchange, ventilatory parameters, haemodynamics, extravascular lung water and indices of ventilator-induced lung injury. Results The simulated patients responded well to both ventilation strategies. Post 24-h investigation period, the APRV arm had similar PF ratios (137 mmHg vs 157 mmHg), lower sub-injury threshold levels of mechanical power (11.9 J/min vs 20.7 J/min) and lower levels of extravascular lung water (501 ml vs 600 ml) compared to conventional LTV. Driving pressure was higher in the APRV group (11.9 cmH2O vs 8.6 cmH2O), but still significantly less than levels associated with increased mortality. Conclusions Appropriate use of APRV may offer casualties with PBLI important mortality-related benefits and should be considered for management of this challenging patient group.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Management of primary blast lung injury: a comparison of airway pressure release versus low tidal volume ventilation

Scott

Das

Haque

et al. 2020

ICMx

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“…A mathematical model of PBLI was used to examine how the heterogeneity of resultant damaged tissue affects gas flow and forces within the parenchyma. 77 Another study has been able to accurately simulate the pathophysiology involved in PBLI, 78 and used this approach to test different MV strategies, concluding that airway pressure release ventilation represented a potentially useful approach in this patient group. 79 Other work has used integrated cardiopulmonary modeling to assess how therapies that mechanically support the cardiovascular system interact with MV, and the implications of these interactions.…”

Section: Other Mechanical Ventilation Contextsmentioning

confidence: 99%

Modeling Mechanical Ventilation In Silico—Potential and Pitfalls

Hannon

Mistry

Das

et al. 2022

Semin Respir Crit Care Med

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Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to “look inside” the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

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“…Application of advanced technologies allow the translation of basic science and in vivo models into high fidelity computational simulations which reduce the need for expensive and logistically difficult physical experiments. The development of a computational model from in vivo data is demonstrated by Haque et al in this issue 14…”

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confidence: 99%