References of "Desaive, Thomas"
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See detailVirtual Trials of the NICE-SUGAR Protocol: The Impact on Performance of Protocol and Protocol Compliance
Uyttendaele, Vincent ULiege; Dickson, Jennifer L.; Shaw, Geoffrey M. et al

in IFAC-PapersOnLine (in press)

Hypoglycaemia, hyperglycaemia and blood glucose (BG) variability are associated with worsened outcomes in critical care. However, NICE-SUGAR trial showed no clinical benefit from intensive insulin therapy ... [more ▼]

Hypoglycaemia, hyperglycaemia and blood glucose (BG) variability are associated with worsened outcomes in critical care. However, NICE-SUGAR trial showed no clinical benefit from intensive insulin therapy. This study compares the table-based NICE-SUGAR and model-based STAR protocols to assess their relative capability to achieve safe, effective control for all patients. Validated virtual patients (n=443) were used to simulate glycaemic outcomes of the NICE-SUGAR and STAR protocols. Key outcomes evaluate tightness and safety of control for all patients: %BG in 80–144 mg/dL range (PTR); Per-Patient Mean BG (PPM_BG); and Incidence of Hypoglycaemia (BG<40 mg/dL). These metrics determine performance overall, for each patient, and safety. Results are assessed for NICE-SUGAR measuring per-protocol (~24/day) and at reported average rate (~3-hourly; ~8/day). STAR measures 1-3-hourly, averaging 12/day. Per-protocol, STAR provided tight control, with higher PTR (90.7% vs. 78.3%) and tighter median [IQR] PPM_BG (112[106-119] vs. 117[106–137] mg/dL), and greater safety from hypoglycaemia (5 (1%) vs. 10 patients (2.5%)) compared to NICE-SUGAR simulations as per protocol. The 5-95th percentile range PPM_BG for NICE-SUGAR (97–185 mg/dL) showed ~5% of NICE-SUGAR patients had mean BG above 180mg/dL matching clinically reported performance. STAR’s 5th-90th PPM_BG percentile range was (97–146 mg/dL). Measuring as recorded clinically, NICE-SUGAR had PTR of 77%, PPM_BG of 122 [110-140] mg/dL and 24(6%) of patients experienced hypoglycaemia. These results match clinically reported values well (mean BG 115 vs. 118 mg/dL clinically vs. simulation, clinically 7% of patients had a hypoglycaemic event). Glycaemic control protocols need to be both safe and effective for all patients before potential clinical benefits can be assessed. NICE-SUGAR clinical results do not match results expected from their protocol, and show reduced safety and performance in comparison to STAR. [less ▲]

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See detailA mathematical model of respiration under protective ventilation and extracorporeal CO2 removal therapy
Habran, Simon ULiege; Desaive, Thomas ULiege; MORIMONT, Philippe ULiege et al

Conference (2017, September 27)

The aim of the present study is to build a mathematical model of the respiratory system connected to an extracorporeal CO2 removal device (ECCO2RD) to optimize the gas exchanges efficiency. The model must ... [more ▼]

The aim of the present study is to build a mathematical model of the respiratory system connected to an extracorporeal CO2 removal device (ECCO2RD) to optimize the gas exchanges efficiency. The model must be simple enough to provide rapid solutions and to estimate specific parameters from available clinical data. But it also must be complex enough to be able to simulate the respiratory system when protective ventilation is used and when this system is assisted by an ECCO2RD. [less ▲]

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See detailMathematical modeling of extracorporeal CO2 removal therapy. A validation carried out on ten pigs
Habran, Simon ULiege; Desaive, Thomas ULiege; MORIMONT, Philippe ULiege et al

in Medical & Biological Engineering & Computing (2017)

The extracorporeal CO2 removal device (ECCO2RD) is used in clinics to treat patients suffering from respiratory failures like acute respiratory distress syn- drome (ARDS) or chronic obstructive pulmonary ... [more ▼]

The extracorporeal CO2 removal device (ECCO2RD) is used in clinics to treat patients suffering from respiratory failures like acute respiratory distress syn- drome (ARDS) or chronic obstructive pulmonary disease (COPD). The aim of this device is to decarboxylate blood externally with low blood flow. A mathematical model is proposed to describe protective ventilation, ARDS, and an extracorporeal CO2 removal therapy (ECCO2RT). The sim- ulations are compared with experimental data carried out on ten pigs. The results show a good agreement between the mathematical simulations and the experimental data, which provides a nice validation of the model. This model is thus able to predict the decrease of PCO2 during ECCO2RT for different blood flows across the extracorporeal lung support. [less ▲]

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See detailUntangling glycaemia and mortality in critical care
Uyttendaele, Vincent ULiege; Dickson, Jennifer L.; Shaw, Geoffrey M. et al

in Critical Care (2017), 21(1), 152

Background: Hyperglycaemia is associated with adverse outcomes in the intensive care unit, and initial studies suggested outcome benefits of glycaemic control (GC). However, subsequent studies often ... [more ▼]

Background: Hyperglycaemia is associated with adverse outcomes in the intensive care unit, and initial studies suggested outcome benefits of glycaemic control (GC). However, subsequent studies often failed to replicate these results, and they were often unable to achieve consistent, safe control, raising questions about the benefit or harm of GC as well as the nature of the association of glycaemia with mortality and clinical outcomes. In this study, we evaluated if non-survivors are harder to control than survivors and determined if glycaemic outcome is a function of patient condition and eventual outcome or of the glycaemic control provided. Methods: Clinically validated, model-based, hour-to-hour insulin sensitivity (SI) and its hour-to-hour variability (%ΔSI) were identified over the first 72 h of therapy in 145 patients (119 survivors, 26 non-survivors). In hypothesis testing, we compared distributions of SI and %ΔSI in 6-hourly blocks for survivors and non-survivors. In equivalence testing, we assessed if differences in these distributions, based on blood glucose measurement error, were clinically significant. Results: SI level was never equivalent between survivors and non-survivors (95% CI of percentage difference in medians outside ±12%). Non-survivors had higher SI, ranging from 9% to 47% higher overall in 6-h blocks, and this difference became statistically significant as glycaemic control progressed. %ΔSI was equivalent between survivors and non-survivors for all 6-hourly blocks (95% CI of difference in medians within ±12%) and decreased in general over time as glycaemic control progressed. Conclusions: Whereas non-survivors had higher SI levels, variability was equivalent to that of survivors over the first 72 h. These results indicate survivors and non-survivors are equally controllable, given an effective glycaemic control protocol, suggesting that glycaemia level and variability, and thus the association between glycaemia and outcome, are essentially determined by the control provided rather than by underlying patient or metabolic condition. [less ▲]

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See detailImproved Blood Glucose Forecasting Models using Changes in Insulin Sensitivity in Intensive Care Patients
Uyttendaele, Vincent ULiege; Dickson, Jennifer; Shaw, Geoff et al

Poster (2017, February 01)

Introduction: Hyperglycaemia, hypoglycaemia and glycaemic variability are associated with worsened outcomes and increased mortality in intensive care units. Glycaemic control (GC) using insulin therapy ... [more ▼]

Introduction: Hyperglycaemia, hypoglycaemia and glycaemic variability are associated with worsened outcomes and increased mortality in intensive care units. Glycaemic control (GC) using insulin therapy has shown improved outcomes, but have been proven difficult to repeat or achieve safely. STAR (Stochastic TARgeted) is a model-based glycaemic control protocol using a stochastic model to forecast distributions of likely future changes in insulin sensitivity (SI) based on its current value. This can be used to determine likely future blood glucose (BG) levels for a given intervention, enabling the most optimal dose selection that best overlaps a clinically defined BG target band. This study presents a novel 3D model capable to predict likely future distribution of SI using both current SI and its prior variability (%ΔSI). Methods: Metabolic data from 3 clinical ICU cohorts totalling 819 episodes and 68629 hours of treatment under STAR and SPRINT protocols are used in this study. Data triplets (%ΔSIn, SIn, SIn+1) are created and binned together in a range of %ΔSI = [-100%, 200%] and SIn = [1.0e-7, 2.1e-3] in bin sizes of %ΔSI = 10% and SIn = 0.5e-4. The 5th, 50th, and 95th percentile of SIn+1 are determined for each bin where data density is high enough (>100 triplets) and compared to the previous stochastic model. The predictive power of the two models are compared by computing median [IQR] per-patient percentage prediction of SI within the 5th-95th and 25th-75th percentile ranges of model predictions. Results: Results show the previous model is over-conservative for ~77% of the data, mainly where %ΔSI is within an absolute 25% change. The percentage change in the 90% CI width in this region is reduced by ~25-40%. Conversely, non-conservative regions are also identified, with 90% CI width increased up to ~80%. Predictive power is similar for both model (60.3% [47.8%, 71.5%] vs. 51.2 [42.9%, 59.2%] within 25th-75th and 93.6% [85.7%, 97.3%] vs. 90.7% [84.4%, 94.6%] within 5th-95th range). Conclusions: The new 3D model achieved similar predictive power as the previous model by reducing the 5th-95th percentile prediction range for 77% of the data, predominantly where SI is stable. If the conservatism of the previous model reduces risk of hypoglycaemia, it also inhibits the controller’s ability to reduce BG to the normal range by safely using more aggressive dosing. The 3D new model thus better characterises patient-specific response to insulin, and allows more optimal dosing, increasing performance and safety. [less ▲]

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See detailPractical identifiability analysis of a minimal cardiovascular system model.
Pironet, Antoine; Docherty, Paul D.; Dauby, Pierre ULiege et al

in Computer Methods & Programs in Biomedicine (2017)

BACKGROUND AND OBJECTIVE: Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and ... [more ▼]

BACKGROUND AND OBJECTIVE: Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. METHODS: An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. RESULTS: Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. CONCLUSIONS: This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. [less ▲]

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See detailGeneralisability of a Virtual Trials Method for Glycaemic Control in Intensive Care.
Dickson, Jennifer L.; Stewart, Kent W.; Pretty, Christopher G. et al

in IEEE transactions on bio-medical engineering (2017)

BACKGROUND: Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic ... [more ▼]

BACKGROUND: Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic variability often results in poor BG control and low BG (hypoglycaemia). OBJECTIVE: This paper presents a model-based virtual trial method for glycaemic control protocol design, and evaluates its generalisability across different populations. METHODS: Model-based insulin sensitivity (SI) was used to create virtual patients from clinical data from three different ICUs in New Zealand, Hungary, and Belgium. Glycaemic results from simulation of virtual patients under their original protocol (self-simulation) and protocols from other units (cross-simulation) were compared. RESULTS: Differences were found between the three cohorts in median SI and inter-patient variability in SI. However, hour-to-hour intra-patient variability in SI was found to be consistent between cohorts. Self and cross-simulation results were found to have overall similarity and consistency, though results may differ in the first 24-48 hours due to different cohort starting BG and underlying SI. CONCLUSIONS AND SIGNIFICANCE: Virtual patients and the virtual trial method were found to be generalisable across different ICUs. This virtual trial method is useful for in silico protocol design and testing, given an understanding of the underlying assumptions and limitations of this method. [less ▲]

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See detailMinimally invasive estimation of ventricular dead space volume through use of Frank-Starling curves.
Davidson, Shaun; Pretty, Chris; Pironet, Antoine et al

in PLoS ONE (2017), 12(4), 0176302

This paper develops a means of more easily and less invasively estimating ventricular dead space volume (Vd), an important, but difficult to measure physiological parameter. Vd represents a subject and ... [more ▼]

This paper develops a means of more easily and less invasively estimating ventricular dead space volume (Vd), an important, but difficult to measure physiological parameter. Vd represents a subject and condition dependent portion of measured ventricular volume that is not actively participating in ventricular function. It is employed in models based on the time varying elastance concept, which see widespread use in haemodynamic studies, and may have direct diagnostic use. The proposed method involves linear extrapolation of a Frank-Starling curve (stroke volume vs end-diastolic volume) and its end-systolic equivalent (stroke volume vs end-systolic volume), developed across normal clinical procedures such as recruitment manoeuvres, to their point of intersection with the y-axis (where stroke volume is 0) to determine Vd. To demonstrate the broad applicability of the method, it was validated across a cohort of six sedated and anaesthetised male Pietrain pigs, encompassing a variety of cardiac states from healthy baseline behaviour to circulatory failure due to septic shock induced by endotoxin infusion. Linear extrapolation of the curves was supported by strong linear correlation coefficients of R = 0.78 and R = 0.80 average for pre- and post- endotoxin infusion respectively, as well as good agreement between the two linearly extrapolated y-intercepts (Vd) for each subject (no more than 7.8% variation). Method validity was further supported by the physiologically reasonable Vd values produced, equivalent to 44.3-53.1% and 49.3-82.6% of baseline end-systolic volume before and after endotoxin infusion respectively. This method has the potential to allow Vd to be estimated without a particularly demanding, specialised protocol in an experimental environment. Further, due to the common use of both mechanical ventilation and recruitment manoeuvres in intensive care, this method, subject to the availability of multi-beat echocardiography, has the potential to allow for estimation of Vd in a clinical environment. [less ▲]

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See detailMinimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance.
Davidson, Shaun; Pretty, Chris; Pironet, Antoine et al

in BioMedical Engineering OnLine (2017), 16(1), 42

BACKGROUND: The aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat ... [more ▼]

BACKGROUND: The aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat evolution could add significant new data and insight to improve diagnosis and treatment. The method developed uses the clinically available inputs of aortic pressure, heart rate and baseline end-systolic volume (via echocardiography) to determine the outputs of left ventricular pressure, volume and dead space volume, and thus the TVE curve. This approach avoids directly assuming the shape of the TVE curve, allowing more effective capture of intra- and inter-patient variability. RESULTS: The resulting TVE curve was experimentally validated against the TVE curve as derived from experimentally measured left ventricular pressure and volume in animal models, a data set encompassing 46,318 heartbeats across 5 Pietrain pigs. This simulated TVE curve was able to effectively approximate the measured TVE curve, with an overall median absolute error of 11.4% and overall median signed error of -2.5%. CONCLUSIONS: The use of clinically available inputs means there is potential for real-time implementation of the method at the patient bedside. Thus the method could be used to provide additional, patient specific information on intra- and inter-beat variation in heart function. [less ▲]

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See detailImproved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement.
Kamoi, Shun; Pretty, Christopher; Balmer, Joel et al

in BioMedical Engineering OnLine (2017), 16(1), 51

BACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques ... [more ▼]

BACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. METHODS: This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir-wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20-24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. RESULTS: Bland-Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of +/-26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. CONCLUSION: The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV. [less ▲]

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See detailEffect of citrate anticoagulation on CO2 extraction during low flow extracorporeal veno-venous CO2 removal therapy
MORIMONT, Philippe ULiege; Habran, Simon ULiege; Hubert, Romain et al

in Intensive Care Medicine Experimental (2016), 4

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See detailA Comparison between four Techniques to Measure Cardiac Output
Pironet, Antoine ULiege; Dauby, Pierre ULiege; Chase, J. Geoffrey et al

in Proceedings of the 38th International Conference of the IEEE Engineering in Medicine and Biology Society (2016, August 17)

Cardiac output is an important variable when monitoring hemodynamic status. In particular, changes in cardiac output represent the goal of several circulatory management therapies. Unfortunately, cardiac ... [more ▼]

Cardiac output is an important variable when monitoring hemodynamic status. In particular, changes in cardiac output represent the goal of several circulatory management therapies. Unfortunately, cardiac output is very difficult to estimate, either in experimental or clinical settings. The goal of this work is to compare four techniques to measure cardiac output: pressure-volume catheter, aortic flow probe, thermodilution, and the PiCCO monitor. These four techniques were simultaneously used during experiments of fluid and endotoxin administration on 7 pigs. Findings show that, first, each individual technique is precise, with a relative coefficient of repeatability lower than 7 %. Second, 1 cardiac output estimate provided by any technique relates poorly to the estimates from the other 3, even if there is only small bias between the techniques. Third, changes in cardiac output detected by one technique are only detected by the others in 62 to 100 % of cases. This study confirms the difficulty of obtaining a reliable clinical cardiac output measurement. Therefore, several measurements using different techniques should be performed, if possible, and all such should be treated with caution. [less ▲]

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See detailA Comparison between four Techniques to Measure Cardiac Output
Pironet, Antoine ULiege; Dauby, Pierre ULiege; Chase, J. Geoffrey et al

Poster (2016, August 17)

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See detailModel-Based Decision Support Algorithm to Guide Fluid Resuscitation
Pironet, Antoine ULiege; Dauby, Pierre ULiege; MORIMONT, Philippe ULiege et al

in IFAC-PapersOnLine (2016, July 26), 49(5), 224-229

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See detailModel-Based Decision Support Algorithm to Guide Fluid Resuscitation
Pironet, Antoine ULiege; Dauby, Pierre ULiege; MORIMONT, Philippe ULiege et al

Conference (2016, June 02)

Fluid resuscitation is the first choice therapy for sepctic shock. However, fluid infusion only increases cardiac output in approximately 50 % of cases, while an excess of fluid can have harmful effects ... [more ▼]

Fluid resuscitation is the first choice therapy for sepctic shock. However, fluid infusion only increases cardiac output in approximately 50 % of cases, while an excess of fluid can have harmful effects. Therefore, clinicians are looking for indices to predict the effect of fluid infusion on cardiac output, before giving fluid. In this work, a minimal mathematical model of the cardiovascular system is used, representing the heart, an artery and a vein. The nine model parameters, including total stressed blood volume, are identified from experimental data. The experimental data was recorded during three 500 ml fluid infusions on two pigs infected with endotoxin, to simulate septic shock. The total stressed blood volume parameter is negatively associated with the change in cardiac output after fluid infusion, as observed in previous studies. Subsequently, an algorithm is proposed to guide fluid resuscitation, based on the value of this parameter. The use of the algorithm results in 60 % less fluid being given with virtually no effect on cardiac output. The decision algorithm has the potential to be used in human clinical trials since the data required for parameter identification can be obtained in an intensive care unit. [less ▲]

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See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULiege; Desaive, Thomas ULiege et al

Poster (2016, March 04)

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See detailCardio-pulmonary mechanics and minimal modelling in critical care
de Bournonville, Sébastien; Pironet, Antoine ULiege; Desaive, Thomas ULiege et al

in 14th Belgian Day on Biomedical Engineering (2016, March 04)

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