Modelling: a core technique in anaesthesia and critical care research

Hardman, Jonathan G.; Ross, Jonathan J.

doi:10.1093/bja/ael272

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…As a research technique, the validity of modelling parallels that of clinical trials or laboratory study 9. Non-biological-based research is cheaper than animal modelling, requires less stringent ethical approval and can accommodate scenarios that are unachievable in live animal or human research, such as multiple casualties with multiple injury events.…”

Section: Modelling-based Researchmentioning

confidence: 99%

Modelling primary blast lung injury: current capability and future direction

Scott¹,

Hulse

Haque

et al. 2016

J R Army Med Corps

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Section: Modelling-based Researchmentioning

confidence: 99%

Modelling primary blast lung injury: current capability and future direction

Scott¹,

Hulse

Haque

et al. 2016

J R Army Med Corps

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“…Studies have found conflicting results and recommended different techniques of pre-oxygenation. Computer simulation can be used to undertake precisely controlled investigations difficult or impossible to achieve in vivo [13]. We aimed to use the Nottingham Physiology Simulator to establish the differences between pregnant and non-pregnant women during pre-oxygenation, and the optimal method of pre-oxygenation in pregnancy.…”

mentioning

confidence: 99%

Pre‐oxygenation in pregnancy: an investigation using physiological modelling

2008

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SummaryHypoxaemia during anaesthetic induction in obstetrics is hazardous for mother and baby, but the onset of desaturation can be delayed by pre-oxygenation. This study investigated pre-oxygenation during pregnancy using computer simulation. The Nottingham Physiology Simulator was configured to replicate normal pregnant physiology. Three pregnant and three non-pregnant subjects were created, representing population variation according to published physiological values. They underwent pre-oxygenation by tidal and vital capacity breathing of 100% oxygen. Pre-oxygenation during tidal breathing proceeded more rapidly in pregnancy, the median [range] time to achieve 95% of the maximum change in P É O 2 being 1 min 37 s [1:23-1:52] in pregnant subjects, compared to 2 min 51 s [2:28-3:15] in non-pregnant subjects. Vital capacity pre-oxygenation required seven breaths [5][6][7][8][9][10] in pregnant subjects, compared to six breaths [4][5][6][7][8][9] in non-pregnant subjects, to achieve the same P É O 2 as after 95% complete tidal pre-oxygenation. We recommend 2 min of tidal breathing for pre-oxygenation in pregnancy.

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“…Mathematical modelling and computational simulation are becoming an increasingly important tool in the fields of medicine where in vivo studies are difficult, expensive or impractical [1]. However, a significant factor hampering the wider clinical exploitation of in silico simulation models is the current lack of rigorous procedures for model validation and verification, since doubts about model validity naturally have a strongly negative impact on the clinical applicability of any predictions arising from simulation studies.…”

Section: Introductionmentioning

confidence: 99%

A systems engineering approach to validation of a pulmonary physiology simulator for clinical applications

Das

Gao

Menon

et al. 2010

J. R. Soc. Interface.

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Physiological simulators which are intended for use in clinical environments face harsh expectations from medical practitioners; they must cope with significant levels of uncertainty arising from non-measurable parameters, population heterogeneity and disease heterogeneity, and their validation must provide watertight proof of their applicability and reliability in the clinical arena. This paper describes a systems engineering framework for the validation of an in silico simulation model of pulmonary physiology. We combine explicit modelling of uncertainty/variability with advanced global optimization methods to demonstrate that the model predictions never deviate from physiologically plausible values for realistic levels of parametric uncertainty. The simulation model considered here has been designed to represent a dynamic in vivo cardiopulmonary state iterating through a mass-conserving set of equations based on established physiological principles and has been developed for a direct clinical application in an intensive-care environment. The approach to uncertainty modelling is adapted from the current best practice in the field of systems and control engineering, and a range of advanced optimization methods are employed to check the robustness of the model, including sequential quadratic programming, mesh-adaptive direct search and genetic algorithms. An overview of these methods and a comparison of their reliability and computational efficiency in comparison to statistical approaches such as Monte Carlo simulation are provided. The results of our study indicate that the simulator provides robust predictions of arterial gas pressures for all realistic ranges of model parameters, and also demonstrate the general applicability of the proposed approach to model validation for physiological simulation.

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Modelling: a core technique in anaesthesia and critical care research

Cited by 10 publications

References 26 publications

Modelling primary blast lung injury: current capability and future direction

Modelling primary blast lung injury: current capability and future direction

Pre‐oxygenation in pregnancy: an investigation using physiological modelling

A systems engineering approach to validation of a pulmonary physiology simulator for clinical applications

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