Does tight glycemic control positively impact on patient mortality?

peer reviewe

Pilot Trials of STAR Target to Range Glycemic Control

ESICM 2011 programme is available in files INTRODUCTION. Tight glycemic control (TGC) has shown benefits in cardiac surgery ICU patients. STAR (Stochastic TARgeted) is a flexible, model-based TGC protocol accounting for patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) below 90 mg/dL. OBJECTIVES. To assess the safety, efficacy and clinical workload of the STAR TGC controller in pilot trials

Model-based cardiovascular monitoring of acute pulmonary embolism in porcine trials

Introduction: Diagnosis and treatment of cardiac and circulatory dysfunction can be error-prone and relies heavily on clinical intuition and experience. Model-based approaches utilising measurements available in the Intensive care unit (ICU) can provide a clearer physiological picture of a patient’s cardiovascular status to assist medical staff with diagnosis and therapy decisions. This research tests a subject-specific cardiovascular system (CVS) modelling technique on measurements from a porcine model of acute pulmonary embolism (APE). Methods: Measurements were recorded in 5 pig trials, where autologous blood clots were inserted every two hours into the jugular vein to simulate pulmonary emboli. Of these measurements only a minimal set of clinically available or inferable data were used in the identification process (aortic and pulmonary artery pressure, stroke volume, heart rate, global end diastolic volume, and mitral and tricuspid valve closure times). The CVS model was fitted to 46 sets of data taken at 30 minute intervals (t=0, 30, 60, …, 270) during the induction of APE to identify physiological model parameters and their change over time in APE. Model parameters and outputs were compared to experimentally derived metrics and measurements not used in the identification method to validate the accuracy of the model and assess its diagnostic capability. Results: Modelled mean ventricular volumes and maximum ventricular pressures matched measured values with median absolute errors of 4.3% and 4.4%, which are less than experimental measurement noise (~10%). An increase in pulmonary vascular resistance, the main hemodynamic consequence of APE, was identified in all the pigs and related well to experimental values (R=0.68). Detrimental changes in reflex responses, such as decreased right ventricular contractility, were noticed in two pigs that died during the trial, diagnosing the loss of autonomous control. Increases in the ratio of the modelled right to left ventricular end diastolic volumes, signifying the leftward shift of the intra-ventricular septum seen in APE, compared well to the clinically measured index (R=0.88). Conclusions: Subject-specific CVS models can accurately and continuously diagnose and track acute disease dependent cardiovascular changes resulting from APE using readily available measurements. Human trials are underway to clinically validate these animal trial results

Pulmonary embolism diagnostics from the driver function

Ventricular driver functions are not readily measured in the ICU, but can clearly indicate the development of pulmonary embolism (PE) otherwise difficult to diagnose. Recent work has developed accurate methods of measuring these driver functions from readily available ICU measurements. This research tests those methods by assessing the ability of these driver functions to diagnose the evolution of PE

Enhanced insulin sensitivity variability in the first 3 days of ICU stay: implications for tight glycemic control

Effective tight glycemic control (TGC) can improve outcomes, particularly in cardiovascular surgery, but is difficult to achieve. Variability in insulin sensitivity/resistance resulting from the level and evolution of stress response, particularly early in a patient’s stay, can lead to hyperglycemia and variability, which are associated with mortality. This study quantifies the daily evolution of the variability of insulin sensitivity for cardiovascular surgical and all other ICU patients

Amplitude equations for Rayleigh-Benard convective rolls far from threshold

An extension of the amplitude method is proposed. An iterative algorithm is developed to build an amplitude equation model that is shown to provide precise quantitative results even far from the linear instability threshold. The method is applied to the study of stationary Rayleigh-Benard thermoconvective rolls in the nonlinear regime. In particular, the generation of second and third spatial harmonics is analyzed. Comparison with experimental results and direct numerical calculations is also made and a very good agreement is found.Peer reviewe

Effect of various Neurally adjusted ventilatory assist (NAVA) gains on the relationship between diaphragmatic activity (Eadi max) and tidal volume (Vt)

ESICM 2011 programme is available in notes http://www.springerlink.com/content/m0xth64u3885w270/</a

Next-generation, personalised, model-based critical care medicine : a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

© 2018 The Author(s). Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care