Cumulative time in band (cTIB): glycemic level, variability and patient outcome all in onePenning, Sophie ; ; et alConference (2012, October 15) Detailed reference viewed: 22 (1 ULg) Cumulative Time in Band (cTIB): Glycemic Level, Variability and Patient Outcome All in 1Penning, Sophie ; ; et alin Intensive Care Medicine (2012, October), 38 (Suppl 1) Detailed reference viewed: 21 (1 ULg) Second pilot trials of the STAR-Liege protocol for tight glycemic control in critically ill patientsPenning, Sophie ; ; MASSION, Paul et alin BioMedical Engineering OnLine (2012) Detailed reference viewed: 18 (3 ULg) Interstitial kinetic parameters for a 2-compartment insulin model with saturable clearancePretty, Christopher ; ; et alConference (2012, August) Detailed reference viewed: 20 (1 ULg) Impact of sensor and measurement timing errors on model-based insulin sensitivityPretty, Christopher ; ; et alConference (2012, August) Detailed reference viewed: 1 (0 ULg) Interstitial kinetic parameters for a 2-compartment insulin model with saturable clearancePretty, Christopher ; ; et alin Proceedings of the 8th IFAC Symposium on Biological and Medical Systems (2012, August) Detailed reference viewed: 1 (0 ULg) Impact of sensor and measurement timing errors on model-based insulin sensitivityPretty, Christopher ; ; et alin Proceedings of the 8th IFAC Symposium on Biological and Medical Systems (2012, August) Detailed reference viewed: 3 (1 ULg) Development and Pilot Trial Results of Stochastic Targeted (STAR) Glycemic Control in a Medical ICU; ; et al in Proceedings of the 8th IFAC Symposium on Biological and Medical Systems (2012, August) Detailed reference viewed: 15 (2 ULg) Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic controlPretty, Christopher ; ; et alin Annals of Intensive Care (2012) Introduction: Effective tight glycaemic control (TGC) can improve outcomes in critical care patients, but is difficult to achieve consistently. Insulin sensitivity defines the metabolic balance between ... [more ▼] Introduction: Effective tight glycaemic control (TGC) can improve outcomes in critical care patients, but is difficult to achieve consistently. Insulin sensitivity defines the metabolic balance between insulin concentration and insulin mediated glucose disposal. Hence, variability of insulin sensitivity can cause variable glycaemia. This study quantifies and compares the daily evolution of insulin sensitivity level and variability for critical care patients receiving TGC. <br /> <br />Methods: A retrospective analysis of data from the SPRINT TGC study involving patients admitted to a mixed medical-surgical ICU between August 2005 and May 2007. Only patients who commenced TGC within 12 hours of ICU admission and spent at least 24 hours on the SPRINT protocol were included (N=164). Model-based insulin sensitivity (SI) was identified each hour. Absolute level and hour-to-hour percent changes in SI were assessed on cohort and per-patient bases. Levels and variability of SI were compared over time on 24-hour and 6-hour timescales for the first 4 days of ICU stay. <br /> <br />Results: Cohort and per-patient median SI levels increased by 34% and 33% (p<0.001) between days 1 and 2 of ICU stay. Concomitantly, cohort and per-patient SI variability decreased by 32% and 36% (p<0.001). For 72% of the cohort, median SI on day 2 was higher than on day 1. The day 1-2 results are the only clear, statistically significant trends across both analyses. <br /> <br />Analysis of the first 24 hours using 6-hour blocks of SI data showed that most of the improvement in insulin sensitivity level and variability seen between days 1 and 2 occurred during the first 12-18 hours of day 1. <br /> <br />Conclusions: Critically ill patients have significantly lower and more variable insulin sensitivity on day 1 than later in their ICU stay and particularly during the first 12 hours. This rapid improvement is likely due to the decline of counter-regulatory hormones as the acute phase of critical illness progresses. Clinically, these results suggest that while using TGC protocols with patients during their first few days of ICU stay, extra care should be afforded. Increased measurement frequency, higher target glycaemic bands, conservative insulin dosing and modulation of carbohydrate nutrition should be considered to safely minimize outcome glycaemic variability and reduce the risk of hypoglycaemia. [less ▲] Detailed reference viewed: 32 (18 ULg) Does Tight Glycemic Control positively impact on patient mortality?Penning, Sophie ; ; et alPoster (2012, March 20) Detailed reference viewed: 7 (5 ULg) Does Tight Glycemic Control positively impact on patient mortality?Penning, Sophie ; ; et alin Critical Care (2012, March 20) Detailed reference viewed: 8 (4 ULg) STAR Development and Protocol Comparison; ; et al in IEEE Transactions on Biomedical Engineering (2012) Detailed reference viewed: 5 (1 ULg) Beat-to-beat estimation of the continuous left and right cardiac elastance from metrics commonly available in clinical settings.; ; et al in BioMedical Engineering OnLine (2012), 11(1), 73 ABSTRACT: INTRODUCTION: : Functional time-varying cardiac elastances (FTVE) contain a rich amount of information about the specific cardiac state of a patient. However, a FTVE waveform is very invasive to ... [more ▼] ABSTRACT: INTRODUCTION: : Functional time-varying cardiac elastances (FTVE) contain a rich amount of information about the specific cardiac state of a patient. However, a FTVE waveform is very invasive to directly measure, and is thus currently not used in clinical practice. This paper presents a method for the estimation of a patient specific FTVE, using only metrics that are currently available in a clinical setting. METHOD: : Correlations are defined between invasively measured FTVE waveforms and the aortic and pulmonary artery pressures from 2 cohorts of porcine subjects, 1 induced with pulmonary embolism, the other with septic shock. These correlations are then used to estimate the FTVE waveform based on the individual aortic and pulmonary artery pressure waveforms, using the "other" dysfunction's correlations as a cross validation. RESULTS: : The cross validation resulted in 1.26% and 2.51% median errors for the left and right FTVE respectively on pulmonary embolism, while the septic shock cohort had 2.54% and 2.90% median errors. CONCLUSIONS: : The presented method accurately and reliably estimated a patient specific FTVE, with no added risk to the patient. The cross validation shows that the method is not dependent on dysfunction and thus has the potential for generalisation beyond pulmonary embolism and septic shock. [less ▲] Detailed reference viewed: 16 (2 ULg) Interface Design and Human Factors Consideration for Model-Based Tight Glycemic Control in Critical Care; ; et al in Journal of Diabetes Science and Technology (2012) Detailed reference viewed: 10 (2 ULg) Stochastic Targeted (STAR) Glycemic Control - Design, Safety and Performance; ; et al in Journal of Diabetes Science and Technology (2012) Detailed reference viewed: 12 (3 ULg) Data Entry Errors and Design for Model-Based Tight Glycemic Control in Critical Care; ; et al in Journal of Diabetes Science and Technology (2012) Detailed reference viewed: 10 (8 ULg) Tight Glycemic Control in Critically Ill Patients: the STAR FrameworkPenning, Sophie ; Desaive, Thomas ; MASSION, Paul et alPoster (2011, October) Detailed reference viewed: 18 (6 ULg) Enhanced insulin sensitivity variability in the first 3 days of ICU stay: Implications for TGC; ; Penning, Sophie et alin Critical Care (2011, March) Detailed reference viewed: 10 (7 ULg) Validation of a virtual patient and virtual trials method for accurate prediction of TGC protocol performance; ; Penning, Sophie et alin Critical Care (2011, March) Detailed reference viewed: 15 (8 ULg) |
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