References of "Chase, J. Geoffrey"
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See detailStructural identifiability analysis of a cardiovascular system model
Pironet, Antoine ULg; Dauby, Pierre ULg; Chase, J. Geoffrey et al

Conference (2014, August)

A simple experimentally validated cardiovascular system model has been shown to be able to track the evolution of various diseases. The model has previously been made patient-specific by adjustment of its ... [more ▼]

A simple experimentally validated cardiovascular system model has been shown to be able to track the evolution of various diseases. The model has previously been made patient-specific by adjustment of its parameters on the basis of a minimal set of hemodynamic measurements. However, this model has not yet been shown to be structurally identifiable, which means that the adjusted model parameters may not be unique. The model equations were manipulated to show that, from a theoretical point of view, all of their parameters can be exactly retrieved from a restricted set of model outputs. However, this set of model outputs is still too large for a clinical application, because it includes left and right ventricular pressures. Consequently, further hypotheses that determine some model parameter values have to be made for the model to be clinically applicable. [less ▲]

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See detailStructural Identifiability Analysis of a Cardiovascular System Model
Pironet, Antoine ULg; Dauby, Pierre ULg; Chase, J. Geoffrey et al

in Preprints of the 19th World Congress (2014, August)

A simple experimentally validated cardiovascular system model has been shown to be able to track the evolution of various diseases. The model has previously been made patient-specific by adjustment of its ... [more ▼]

A simple experimentally validated cardiovascular system model has been shown to be able to track the evolution of various diseases. The model has previously been made patient-specific by adjustment of its parameters on the basis of a minimal set of hemodynamic measurements. However, this model has not yet been shown to be structurally identifiable, which means that the adjusted model parameters may not be unique. The model equations were manipulated to show that, from a theoretical point of view, all of their parameters can be exactly retrieved from a restricted set of model outputs. However, this set of model outputs is still too large for a clinical application, because it includes left and right ventricular pressures. Consequently, further hypotheses that determine some model parameter values have to be made for the model to be clinically applicable. [less ▲]

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See detailSurvey about diffusion and adoption of glycaemic controller in European intensive care units
Penning, Sophie ULg; Pironet, Antoine ULg; Chase, J. Geoffrey et al

Conference (2014, August)

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See detailSurvey about diffusion and adoption of glycaemic controller in European intensive care units
Penning, Sophie ULg; Pironet, Antoine ULg; Chase, J. Geoffrey et al

in Proceedings of the 19th IFAC Conference (2014, August)

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See detailInsulin Sensitivity Variability during Hypothermia
Sah Pri, Azurahisham; Chase, J. Geoffrey; Pretty, Christopher et al

in Proceedings of the 19th IFAC Conference (2014, August)

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See detailDoes the achievement of an intermediate glycemic target reduce organ failure and mortality? A post-hoc analysis of the Glucontrol Trial
Penning, Sophie ULg; Chase, J. Geoffrey; Preiser, Jean-Charles et al

in Journal of Critical Care (2014)

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See detailReducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol.
Thomas, Felicity; Pretty, Christopher G.; Fisk, Liam et al

in Biomedical engineering online (2014), 13

BACKGROUND: The metabolism of critically ill patients evolves dynamically over time. Post critical insult, levels of counter-regulatory hormones are significantly elevated, but decrease rapidly over the ... [more ▼]

BACKGROUND: The metabolism of critically ill patients evolves dynamically over time. Post critical insult, levels of counter-regulatory hormones are significantly elevated, but decrease rapidly over the first 12-48 hours in the intensive care unit (ICU). These hormones have a direct physiological impact on insulin sensitivity (SI). Understanding the variability of SI is important for safely managing glycaemic levels and understanding the evolution of patient condition. The objective of this study is to assess the evolution of SI over the first two days of ICU stay, and using this data, propose a separate stochastic model to reduce the impact of SI variability during glycaemic control using the STAR glycaemic control protocol. METHODS: The value of SI was identified hourly for each patient using a validated physiological model. Variability of SI was then calculated as the hour-to-hour percentage change in SI. SI was examined using 6 hour blocks of SI to display trends while mitigating the effects of noise. To reduce the impact of SI variability on achieving glycaemic control a new stochastic model for the most variable period, 0-18 hours, was generated. Virtual simulations were conducted using an existing glycaemic control protocol (STAR) to investigate the clinical impact of using this separate stochastic model during this period of increased metabolic variability. RESULTS: For the first 18 hours, over 80% of all SI values were less than 0.5 x 10(-3) L/mU x min, compared to 65% for >18 hours. Using the new stochastic model for the first 18 hours of ICU stay reduced the number of hypoglycaemic measurements during virtual trials. For time spent below 4.4, 4.0, and 3.0 mmol/L absolute reductions of 1.1%, 0.8% and 0.1% were achieved, respectively. No severe hypoglycaemic events (BG < 2.2 mmol/L) occurred for either case. CONCLUSIONS: SI levels increase significantly, while variability decreases during the first 18 hours of a patients stay in ICU. Virtual trials, using a separate stochastic model for this period, demonstrated a reduction in variability and hypoglycaemia during the first 18 hours without adversely affecting the overall level of control. Thus, use of multiple models can reduce the impact of SI variability during model-based glycaemic control. [less ▲]

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See detailWhen the value of gold is zero.
Chase, J. Geoffrey; Moeller, Knut; Shaw, Geoffrey M. et al

in BMC research notes (2014), 7

This manuscript presents the concerns around the increasingly common problem of not having readily available or useful "gold standard" measurements. This issue is particularly important in critical care ... [more ▼]

This manuscript presents the concerns around the increasingly common problem of not having readily available or useful "gold standard" measurements. This issue is particularly important in critical care where many measurements used in decision making are surrogates of what we would truly wish to use. However, the question is broad, important and applicable in many other areas.In particular, a gold standard measurement often exists, but is not clinically (or ethically in some cases) feasible. The question is how does one even begin to develop new measurements or surrogates if one has no gold standard to compare with?We raise this issue concisely with a specific example from mechanical ventilation, a core bread and butter therapy in critical care that is also a leading cause of length of stay and cost of care. Our proposed solution centers around a hierarchical validation approach that we believe would ameliorate ethics issues around radiation exposure that make current gold standard measures clinically infeasible, and thus provide a pathway to create a (new) gold standard. [less ▲]

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See detailContinuous stroke volume estimation from aortic pressure using zero dimensional cardiovascular model: proof of concept study from porcine experiments.
Kamoi, Shun; Pretty, Christopher; Docherty, Paul et al

in PloS one (2014), 9(7), 102476

INTRODUCTION: Accurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. However, direct ... [more ▼]

INTRODUCTION: Accurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. However, direct measurements are highly invasive in clinical practice, and current procedures for estimating SV require specialized devices and significant approximation. METHOD: This study investigates the accuracy of a three element Windkessel model combined with an aortic pressure waveform to estimate SV. Aortic pressure is separated into two components capturing; 1) resistance and compliance, 2) characteristic impedance. This separation provides model-element relationships enabling SV to be estimated while requiring only one of the three element values to be known or estimated. Beat-to-beat SV estimation was performed using population-representative optimal values for each model element. This method was validated using measured SV data from porcine experiments (N = 3 female Pietrain pigs, 29-37 kg) in which both ventricular volume and aortic pressure waveforms were measured simultaneously. RESULTS: The median difference between measured SV from left ventricle (LV) output and estimated SV was 0.6 ml with a 90% range (5th-95th percentile) -12.4 ml-14.3 ml. During periods when changes in SV were induced, cross correlations in between estimated and measured SV were above R = 0.65 for all cases. CONCLUSION: The method presented demonstrates that the magnitude and trends of SV can be accurately estimated from pressure waveforms alone, without the need for identification of complex physiological metrics where strength of correlations may vary significantly from patient to patient. [less ▲]

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See detailA patient-specific airway branching model for mechanically ventilated patients.
Damanhuri, Nor Salwa; Docherty, Paul D.; Chiew, Yeong Shiong et al

in Computational and mathematical methods in medicine (2014), 2014

Background. Respiratory mechanics models have the potential to guide mechanical ventilation. Airway branching models (ABMs) were developed from classical fluid mechanics models but do not provide accurate ... [more ▼]

Background. Respiratory mechanics models have the potential to guide mechanical ventilation. Airway branching models (ABMs) were developed from classical fluid mechanics models but do not provide accurate models of in vivo behaviour. Hence, the ABM was improved to include patient-specific parameters and better model observed behaviour (ABMps). Methods. The airway pressure drop of the ABMps was compared with the well-accepted dynostatic algorithm (DSA) in patients diagnosed with acute respiratory distress syndrome (ARDS). A scaling factor (alpha) was used to equate the area under the pressure curve (AUC) from the ABMps to the AUC of the DSA and was linked to patient state. Results. The ABMps recorded a median alpha value of 0.58 (IQR: 0.54-0.63; range: 0.45-0.66) for these ARDS patients. Significantly lower alpha values were found for individuals with chronic obstructive pulmonary disease (P < 0.001). Conclusion. The ABMps model allows the estimation of airway pressure drop at each bronchial generation with patient-specific physiological measurements and can be generated from data measured at the bedside. The distribution of patient-specific alpha values indicates that the overall ABM can be readily improved to better match observed data and capture patient condition. [less ▲]

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See detailInterstitial insulin kinetic parameters for a 2-compartment insulin model with saturable clearance
Pretty, Christopher G.; Le Compte, Aaron; Penning, Sophie ULg et al

in Computer Methods & Programs in Biomedicine (2014)

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See detailImpact of sensor and measurement timing errors on model-based insulin sensitivity
Pretty, Christopher ULg; Signal, Matthew; Fisk, Liam et al

in Computer Methods & Programs in Biomedicine (2013)

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See detailInsulin Sensitivity during Hypothermia in Critically Ill Patients
Sah Pri, Azurahisham; Chase, J. Geoffrey; Le Compte, Aaron J. et al

Poster (2013, September)

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See detailSimulation of Left Atrial Function Using a Multi-Scale Model of the Cardiovascular System
Pironet, Antoine ULg; Dauby, Pierre ULg; Paeme, Sabine ULg et al

in PLoS ONE (2013), 8(6), 65146

During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to ... [more ▼]

During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors. [less ▲]

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See detailEvaluation of a Model-Based Hemodynamic Monitoring Method in a Porcine Study of Septic Shock
Revie, James; Stevenson, David; Chase, J. Geoffrey et al

in Computational and Mathematical Methods in Medicine (2013)

Detailed reference viewed: 23 (7 ULg)