References of "Desaive, Thomas"
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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 detailVentriculo-Arterial Coupling: an ideal problem for collaboration between clinicians and engineers
MORIMONT, Philippe ULg; Desaive, Thomas ULg; Chase et al

in Proceedings of CONTROL 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 detailNAVA enhances ventilatory variability and diaphragmatic activity/tidal volume coupling
Moorhead, KT; Piquilloud, L.; Desaive, Thomas ULg et al

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

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See detailEffect of various Neurally adjusted ventilatory assist (NAVA) gains on the relationship between diaphragmatic activity (Eadi max) and tidal volume
Chiew, YS; Piquilloud, L.; Desaive, Thomas ULg et al

in Intensive Care Medicine (2010), 37 (Suppl 1)

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See detailThe future of glycaemic control in critically ill patients requires a close collaboration between bio-engineers and clinicians
Preiser, JC; Desaive, Thomas ULg; Chase, JG

in Proceedings of CONTROL 2010 (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 detailModel-based assessment of ventricular contractility
Desaive, Thomas ULg; Hann, CE; Chase, JG

in Proceedings of the 19th International Conference of the Cardiovascular System Dynamics Society (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 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 detailWhat makes tight glycemic control tight? The impact of variability and nutrition in two clinical studies.
Suhaimi, Fatanah; Le Compte, Aaron; Preiser, Jean-Charles ULg et al

in Journal of Diabetes Science and Technology (2010), 4(2), 284-98

INTRODUCTION: Tight glycemic control (TGC) remains controversial while successful, consistent, and effective protocols remain elusive. This research analyzes data from two TGC trials for root causes of ... [more ▼]

INTRODUCTION: Tight glycemic control (TGC) remains controversial while successful, consistent, and effective protocols remain elusive. This research analyzes data from two TGC trials for root causes of the differences achieved in control and thus potentially in glycemic and other outcomes. The goal is to uncover aspects of successful TGC and delineate the impact of differences in cohorts. METHODS: A retrospective analysis was conducted using records from a 211-patient subset of the GluControl trial taken in Liege, Belgium, and 393 patients from Specialized Relative Insulin Nutrition Titration (SPRINT) in New Zealand. Specialized Relative Insulin Nutrition Titration targeted 4.0-6.0 mmol/liter, similar to the GluControl A (N = 142) target of 4.4-6.1 mmol/liter. The GluControl B (N = 69) target was 7.8-10.0 mmol/liter. Cohorts were matched by Acute Physiology and Chronic Health Evaluation II score and percentage males (p > .35); however, the GluControl cohort was slightly older (p = .011). Overall cohort and per-patient comparisons (median, interquartile range) are shown for (a) glycemic levels achieved, (b) nutrition from carbohydrate (all sources), and (c) insulin dosing for this analysis. Intra- and interpatient variability were examined using clinically validated model-based insulin sensitivity metric and its hour-to-hour variation. RESULTS: Cohort blood glucose were as follows: SPRINT, 5.7 (5.0-6.6) mmol/liter; GluControl A, 6.3 (5.3-7.6) mmol/liter; and GluControl B, 8.2 (6.9-9.4) mmol/liter. Insulin dosing was 3.0 (1.0-3.0), 1.5 (0.5-3), and 0.7 (0.0-1.7) U/h, respectively. Nutrition from carbohydrate (all sources) was 435.5 (259.2-539.1), 311.0 (0.0-933.1), and 622.1 (103.7-1036.8) kcal/day, respectively. Median per-patient results for blood glucose were 5.8 (5.3-6.4), 6.4 (5.9-6.9), and 8.3 (7.6-8.8) mmol/liter. Insulin doses were 3.0 (2.0-3.0), 1.5 (0.8-2.0), and 0.5 (0.0-1.0) U/h. Carbohydrate administration was 383.6 (207.4-497.7), 103.7 (0.0-829.4), and 207.4 (0.0-725.8) kcal/day. Overall, SPRINT gave approximately 2x more insulin with a 3-4x narrower, but generally non-zero, range of nutritional input to achieve equally TGC with less hypoglycemia. Specialized Relative Insulin Nutrition Titration had much less hypoglycemia (<2.2 mmol/liter), with 2% of patients, compared to GluControl A (7.7%) and GluControl B (2.9%), indicating much lower variability, with similar results for glucose levels <3.0 mmol/liter. Specialized Relative Insulin Nutrition Titration also had less hyperglycemia (>8.0 mmol/liter) than groups A and B. GluControl patients (A+B) had a approximately 2x wider range of insulin sensitivity than SPRINT. Hour-to-hour variation was similar. Hence GluControl had greater interpatient variability but similar intrapatient variability. CONCLUSION: Protocols that dose insulin blind to carbohydrate administration can suffer greater outcome glycemic variability, even if average cohort glycemic targets are met. While the cohorts varied significantly in model-assessed insulin resistance, their variability was similar. Such significant intra- and interpatient variability is a further significant cause and marker of glycemic variability in TGC. The results strongly recommended that TGC protocols be explicitly designed to account for significant intra- and interpatient variability in insulin resistance, as well as specifying or having knowledge of carbohydrate administration to minimize variability in glycemic outcomes across diverse cohorts and/or centers. [less ▲]

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See detailNAVA enhances ventilatory variability and diaphragmaticactivity/tidal volume coupling
Moorhead, K.; Piquilloud, L.; Desaive, Thomas ULg et al

in Intensive Care Medicine (2010), 36(2), 326-326

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See detailReduced organ failure with effective glycemic control
Preiser, Jean-Charles; Chase, J. G.; Pretty, C. G. et al

in Intensive Care Medicine (2010), 36(2), 173-173

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