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See detailProcessing aortic and pulmonary artery waveforms to derive the ventricle time-varying elastance
Stevenson, D; Chase, JG; Hann, CE et al

in Proceedings of the 18th IFAC World Congress, 2011 (2011)

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See detailSafety and Performance of Stochastic Targeted (STAR) TGC of Insulin and Nutrition
Shaw, GM; Le Compte, Aaron; Evans, A et al

in Proceedings of SQAO 2011 (2011)

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See detailModel-based diagnosis of acute pulmonary embolism and septic shock in porcine trials
Revie, JA; Stevenson, D; Chase, JG et al

in Proceedings of the Health Research Society of Christchurch Annual Scientific Session 2011 (2011)

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See detailEnteral nutrition-associated incretin effect in the critically ill
Preiser, JC; Jamaludin, U; Docherty, P et al

in Proceedings of the 33rd Congress of Clinical Nutrition and Metabolism (ESPEN 2011) (2011)

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See detailObservation of the Incretin Effect in Critically Ill patients
Jamaludin, U.; Docherty, P; Chase, JG et al

in Proceedings of the 11th Annual Diabetes Technology Meeting (DTM2011) (2011)

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See detailValidation of subject-specific cardiovascular system models from porcine measurements.
Revie, J. A.; Stevenson, D. J.; Chase, J. G. et al

in Computer Methods & Programs in Biomedicine (2011)

A previously validated mathematical model of the cardiovascular system (CVS) is made subject-specific using an iterative, proportional gain-based identification method. Prior works utilised a complete set ... [more ▼]

A previously validated mathematical model of the cardiovascular system (CVS) is made subject-specific using an iterative, proportional gain-based identification method. Prior works utilised a complete set of experimentally measured data that is not clinically typical or applicable. In this paper, parameters are identified using proportional gain-based control and a minimal, clinically available set of measurements. The new method makes use of several intermediary steps through identification of smaller compartmental models of CVS to reduce the number of parameters identified simultaneously and increase the convergence stability of the method. This new, clinically relevant, minimal measurement approach is validated using a porcine model of acute pulmonary embolism (APE). Trials were performed on five pigs, each inserted with three autologous blood clots of decreasing size over a period of four to five hours. All experiments were reviewed and approved by the Ethics Committee of the Medical Faculty at the University of Liege, Belgium. Continuous aortic and pulmonary artery pressures (P(ao), P(pa)) were measured along with left and right ventricle pressure and volume waveforms. Subject-specific CVS models were identified from global end diastolic volume (GEDV), stroke volume (SV), P(ao), and P(pa) measurements, with the mean volumes and maximum pressures of the left and right ventricles used to verify the accuracy of the fitted models. The inputs (GEDV, SV, P(ao), P(pa)) used in the identification process were matched by the CVS model to errors <0.5%. Prediction of the mean ventricular volumes and maximum ventricular pressures not used to fit the model compared experimental measurements to median absolute errors of 4.3% and 4.4%, which are equivalent to the measurement errors of currently used monitoring devices in the ICU ( approximately 5-10%). These results validate the potential for implementing this approach in the intensive care unit. [less ▲]

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See detailPatient specific modelling of cardiac muscle activation
Stevenson, D; Hann, CE; Revie, JA et al

in Proceedings of the Health Research Society of Canterbury (HRSC) Clinical Meeting 2010 (2010)

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See detailModel-based cardiac disease diagnosis in critical care
Revie, JA; Hann, CE; Stevenson, D et al

in Proceedings of the Health Research Society of Canterbury (HRSC) Clinical Meeting 2010 (2010)

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See detailEstimating the driver function of a cardiovascular system model
Stevenson, D; Hann, CE; Chase, JG et al

in Proceedings of CONTROL 2010 (2010)

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See detailA Model-based Approach to Cardiovascular Monitoring of Pulmonary Embolism
Revie, JA; Hann, CE; Stevenson, D et al

in Proceedings of CONTROL 2010 (2010)

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See detailAssessment of ventricular-arterial coupling with a model-based sensor
Desaive, Thomas ULg; LAMBERMONT, Bernard ULg; GHUYSEN, Alexandre ULg et al

in Proceedings of CONTROL 2010 (2010)

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See detailPatient-specific modelling of cardiovascular dysfunction: Identifying models of pulmonary embolism in pigs
Desaive, Thomas ULg; Revie, J; Hann, CE et al

in Proceedings of the 19th International Conference of the Cardiovascular System Dynamics Society (2010)

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See detailThe critical role of carbohydrate administration in safe, effective TGC
Preiser, J-C; Suhaimi, F; Chase, JG et al

in Clinical Nutrition (2010), 5 (Suppl 2):111

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See detailValidation of a virtual trial method for tight glycemic control in intensive care
Suhaimi, F; Chase, JG; Preiser, JC et al

in Proceedings of the Health Research Society of Canterbury (HRSC) Clinical Meeting 2010 (2010)

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See detailReduced Organ Failure with Effective Glycemic Control
Preiser, JC; Chase, JG; Pretty, CG et al

in Intensive Care Medicine (2010), 36 (Suppl 2)

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See detailTight Glycaemic control and nutrition: A comparison of two protocols
Suhaimi, F; Le Compte, AJ; Preiser, JC et al

in Proceedings of the Centre for Bio-Engineering One Day Conference 2010 (2010)

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See detailValidation of a Model-based Virtual Trials Method for Tight Glycaemic Control in Intensive Care
Suhaimi, F; Chase, JG; Le Compte, AJ et al

in Proceedings of the Centre for Bio-Engineering One Day Conference 2010 (2010)

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See detailWhy Protocolised care works in my unit?
Shaw, GM; Chase, JG; Pfeiffer, L et al

in Proceedings of the Australia-New Zealand Intensive Care Society Scientific Meeting (ANZICS 2010) (2010)

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See detailUnique parameter identification for cardiac diagnosis in critical care using minimal data sets.
Hann, C. E.; Chase, J. G.; Desaive, Thomas ULg et al

in Computer Methods & Programs in Biomedicine (2010)

Lumped parameter approaches for modelling the cardiovascular system typically have many parameters of which a significant percentage are often not identifiable from limited data sets. Hence, significant ... [more ▼]

Lumped parameter approaches for modelling the cardiovascular system typically have many parameters of which a significant percentage are often not identifiable from limited data sets. Hence, significant parts of the model are required to be simulated with little overall effect on the accuracy of data fitting, as well as dramatically increasing the complexity of parameter identification. This separates sub-structures of more complex cardiovascular system models to create uniquely identifiable simplified models that are one to one with the measurements. In addition, a new concept of parameter identification is presented where the changes in the parameters are treated as an actuation force into a feed back control system, and the reference output is taken to be steady state values of measured volume and pressure. The major advantage of the method is that when it converges, it must be at the global minimum so that the solution that best fits the data is always found. By utilizing continuous information from the arterial/pulmonary pressure waveforms and the end-diastolic time, it is shown that potentially, the ventricle volume is not required in the data set, which was a requirement in earlier published work. The simplified models can also act as a bridge to identifying more sophisticated cardiac models, by providing an initial set of patient specific parameters that can reveal trends and interactions in the data over time. The goal is to apply the simplified models to retrospective data on groups of patients to help characterize population trends or un-modelled dynamics within known bounds. These trends can assist in improved prediction of patient responses to cardiac disturbance and therapy intervention with potentially smaller and less invasive data sets. In this way a more complex model that takes into account individual patient variation can be developed, and applied to the improvement of cardiovascular management in critical care. [less ▲]

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See detailPatient-specific modelling of the cardiovascular system – application to septic shock with a minimal data set,
Desaive, Thomas ULg; Chase, J. G.; Starfinger, C. et al

in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany (2010)

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