References of "Ghuysen, Alexandre"
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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 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 detailProcessing aortic and pulmonary artery waveforms to derive the ventricle time-varying elastance
Stevenson, D. J.; Hann, C. E.; Chase, G. J. et al

in IFAC Proceedings Volumes (IFAC-PapersOnline) (2011), 18(PART 1), 587-592

Time-varying elastance of the ventricles is an important metric both clinically and as an input for a previously developed cardiovascular model. However, currently time-varying elastance is not normally ... [more ▼]

Time-varying elastance of the ventricles is an important metric both clinically and as an input for a previously developed cardiovascular model. However, currently time-varying elastance is not normally available in an Intensive Care Unit (ICU) setting, as it is an invasive and ethically challenging metric to measure. A previous paper developed a method to map less invasive metrics to the driver function, enabling an estimate to be achieved without invasive measurements. This method requires reliable and accurate processing of the aortic and pulmonary artery pressure waveforms to locate the specific points that are required to estimate the driver function. This paper details the method by which these waveforms are processed, using a data set of five pigs induced with pulmonary embolism, and five pigs induced with septic shock (with haemofiltration), adding up to 88 waveforms (for each of aortic and pulmonary artery pressure), and 616 points in total to locate. 98.2% of all points were located to within 1% of their true value, 0.81% were between 1% and 5%, 0.65% were between 5% and 10%, the remaining 0.32% were below 20%.© 2011 IFAC. [less ▲]

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See detailEfficiency of a French-language triage algorithm in the Emergency Department
JOBE, Jérôme ULg; Ghuysen, Alexandre ULg; GERARD, P et al

in Critical Care Medicine (2011), 15(suppl 1), 455

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See detailClinical detection and monitoring of acute pulmonary embolism: proof of concept of a computer-based method.
Revie, James A; Stevenson, David J; Chase, J Geoffrey et al

in Annals of Intensive Care (2011), 1(1), 33

ABSTRACT: BACKGROUND: The diagnostic ability of computer-based methods for cardiovascular system (CVS) monitoring offers significant clinical potential. This research tests the clinical applicability of a ... [more ▼]

ABSTRACT: BACKGROUND: The diagnostic ability of computer-based methods for cardiovascular system (CVS) monitoring offers significant clinical potential. This research tests the clinical applicability of a newly improved computer-based method for the proof of concept case of tracking changes in important hemodynamic indices due to the influence acute pulmonary embolism (APE). METHODS: Hemodynamic measurements from a porcine model of APE were used to validate the method. Of these measurements, only those that are clinically available or inferable were used in to identify pig-specific computer models of the CVS, including the aortic and pulmonary artery pressure, stroke volume, heart rate, global end diastolic volume, and mitral and tricuspid valve closure times. Changes in the computer-derived parameters were analyzed and compared with experimental metrics and clinical indices to assess the clinical applicability of the technique and its ability to track the disease state. RESULTS: The subject-specific computer models accurately captured the increase in pulmonary resistance (Rpul), the main cardiovascular consequence of APE, in all five pigs trials, which related well (R2 = 0.81) with the experimentally derived pulmonary vascular resistance. An increase in right ventricular contractility was identified, as expected, consistent with known reflex responses to APE. Furthermore, the modeled right ventricular expansion index (the ratio of right to left ventricular end diastolic volumes) closely followed the trends seen in the measured data (R2 = 0.92) used for validation, with sharp increases seen in the metric for the two pigs in a near-death state. These results show that the pig-specific models are capable of tracking disease-dependent changes in pulmonary resistance (afterload), right ventricular contractility (inotropy), and ventricular loading (preload) during induced APE. Continuous, accurate estimation of these fundamental metrics of cardiovascular status can help to assist clinicians with diagnosis, monitoring, and therapy-based decisions in an intensive care environment. Furthermore, because the method only uses measurements already available in the ICU, it can be implemented with no added risk to the patient and little extra cost. CONCLUSIONS: This computer-based monitoring method shows potential for real-time, continuous diagnosis and monitoring of acute CVS dysfunction in critically ill patients. [less ▲]

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See detailLe cas clinique du mois : intoxication accidentelle à dose potentiellement létale d'acide borique
LOMBARD, Xavier ULg; benoit, A.; Ghuysen, Alexandre ULg et al

in Revue Médicale de Liège (2011), 66(12), 608-10

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See detailSubject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: animal experiments and proof of concept.
Chase, J Geoffrey; Lambermont, Bernard ULg; Starfinger, Christina et al

in Physiological Measurement (2011), 32(1), 65-82

A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models ... [more ▼]

A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis-a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases. The main goal of this study is to prove the concept of using only measurements from one side of the heart (right) in a 'minimal' data set to identify an effective patient-specific model that can capture key clinical trends in endotoxic shock. This research extends existing methods to a reduced and minimal data set requiring only a single catheter and reducing the risk of infection and other complications-a very common, typical situation in critical care patients, particularly after cardiac surgery. The extended methods and assumptions that found it are developed and presented in a case study for the patient-specific parameter identification of pig-specific parameters in an animal model of induced endotoxic shock. This case study is used to define the impact of this minimal data set on the quality and accuracy of the model application for monitoring, detecting and diagnosing septic shock. Six anesthetized healthy pigs weighing 20-30 kg received a 0.5 mg kg(-1) endotoxin infusion over a period of 30 min from T0 to T30. For this research, only right heart measurements were obtained. Errors for the identified model are within 8% when the model is identified from data, re-simulated and then compared to the experimentally measured data, including measurements not used in the identification process for validation. Importantly, all identified parameter trends match physiologically and clinically and experimentally expected changes, indicating that no diagnostic power is lost. This work represents a further with human subjects validation for this model-based approach to cardiovascular diagnosis and therapy guidance in monitoring endotoxic disease states. The results and methods obtained can be readily extended from this case study to the other animal model results presented previously. Overall, these results provide further support for prospective, proof of concept clinical testing with humans. [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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See detailValidation of a new French-language triage algorithm : the ELISA scale.
Jobe, Jérôme ULg; Ghuysen, Alexandre ULg; GERARD, P. et al

in Critical Care (2010), 14(Suppl1), 277

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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 detailTime varying elastance estimation in an 8 camber cardiovascular system model
Desaive, Thomas ULg; Chase, J. G.; Hann, C. E. et al

in Intensive Care Medicine (2010), 36(2), 151-151

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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 detailLe couplage ventriculoartériel : du concept aux applications cliniques
Morimont, Philippe ULg; Lambermont, Bernard ULg; Ghuysen, Alexandre ULg et al

in Réanimation (2009), 18(3), 201-206

L’interaction entre le ventricule et le réseau vasculaire est un déterminant majeur de la performance cardiaque globale, particulièrement en présence d’une insuffisance ventriculaire préalable ... [more ▼]

L’interaction entre le ventricule et le réseau vasculaire est un déterminant majeur de la performance cardiaque globale, particulièrement en présence d’une insuffisance ventriculaire préalable. L’évaluation du couplage ventriculoartériel grâce à la mesure de l’élastance ventriculaire, comme reflet de la contractilité et de l’élastance artérielle, en tant qu’indice de post-charge, permet de quantifier cette interaction. Des travaux récents illustrent l’intérêt clinique de ce concept. Jusqu’à présent, son utilisation restait toutefois marginale en raison de la nécessité de recourir à des mesures invasives et complexes. Le développement des techniques d’imagerie non invasive et de traitement des signaux permet actuellement d’envisager l’utilisation de ce concept en pratique clinique courante. [less ▲]

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See detailUnique parameter identification for model-based cardiac diagnosis in critical care
Hann, C. E.; Chase, J. G.; Desaive, Thomas ULg et al

in IFAC Proceedings Volumes (IFAC-PapersOnline) (2009), 7(PART 1), 169-174

Lumped parameter approaches for modeling the cardiovascular system typically have many parameters of which many are not identifiable. The conventional approach is to only identify a small subset of ... [more ▼]

Lumped parameter approaches for modeling the cardiovascular system typically have many parameters of which many are not identifiable. The conventional approach is to only identify a small subset of parameters to match measured data, and to set the remaining parameters at population values. These values are often based on animal data or the "average human" response. The problem, is that setting many parameters at nominal fixed values, may introduce dynamics that are not present in a specific patient. As parameter numbers and model complexity increase, more clinical data is required for validation and the model limitations are harder to quantify. This paper considers the modeling and the parameter identification simultaneously, and creates models that are one to one with the measurements. That is, every input parameter into the model is uniquely optimized to capture the clinical data and no parameters are set at population values. The result is a geometrical characterization of a previously developed six chamber heart model, and a completely patient specific approach to cardiac diagnosis in critical care. In addition, simplified sub-structures of the six chamber model are created to provide very fast and accurate parameter identification from arbitrary starting points and with no prior knowledge on the parameters. Furthermore, by utilizing continuous information from the arterial/pulmonary pressure waveforms and the end-diastolic time, it is shown that only the stroke volumes of the ventricles are required for adequate cardiac diagnosis. This reduced data set is more practical for an intensive care unit as the maximum and minimum volumes are no longer needed, which was a requirement in prior work. The simplified models can also act as a bridge to identifying more sophisticated cardiac models, by providing a generating set of waveforms that the complex models can match to. Most importantly, this approach does not have any predefined assumptions on patient dynamics other than the basic model structure, and is thus suitable for improving cardiovascular management in critical care by optimizing therapy for individual patients. © 2009 IFAC. [less ▲]

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