Glucose control positively influences patient outcome: a retrospective study

The goal of this research is to demonstrate that well-regulated glycemia is beneficial to patient outcome, regardless of how it is achieved

Effects of Neurally Adjusted Ventilatory Assist (NAVA) levels in non-invasive ventilated patients: titrating NAVA levels with electric diaphragmatic activity and tidal volume matching

BACKGROUND: Neurally adjusted ventilatory assist (NAVA) delivers pressure in proportion to diaphragm electrical activity (Eadi). However, each patient responds differently to NAVA levels. This study aims to examine the matching between tidal volume (Vt) and patients' inspiratory demand (Eadi), and to investigate patient-specific response to various NAVA levels in non-invasively ventilated patients. METHODS: 12 patients were ventilated non-invasively with NAVA using three different NAVA levels. NAVA100 was set according to the manufacturer's recommendation to have similar peak airway pressure as during pressure support. NAVA level was then adjusted ±50% (NAVA50, NAVA150). Airway pressure, flow and Eadi were recorded for 15 minutes at each NAVA level. The matching of Vt and integral of Eadi (ʃEadi) were assessed at the different NAVA levels. A metric, Range90, was defined as the 5-95% range of Vt/ʃEadi ratio to assess matching for each NAVA level. Smaller Range90 values indicated better matching of supply to demand. RESULTS: Patients ventilated at NAVA50 had the lowest Range90 with median 25.6 uVs/ml [Interquartile range (IQR): 15.4-70.4], suggesting that, globally, NAVA50 provided better matching between ʃEadi and Vt than NAVA100 and NAVA150. However, on a per-patient basis, 4 patients had the lowest Range90 values in NAVA100, 1 patient at NAVA150 and 7 patients at NAVA50. Robust coefficient of variation for ʃEadi and Vt were not different between NAVA levels. CONCLUSIONS: The patient-specific matching between ʃEadi and Vt was variable, indicating that to obtain the best possible matching, NAVA level setting should be patient specific. The Range90 concept presented to evaluate Vt/ʃEadi is a physiologic metric that could help in individual titration of NAVA level.Peer reviewe

Validation of a virtual patient and virtual trials method for accurate prediction of tight glycemic control protocol performance

Peer reviewe

Variability of insulin sensitivity during the first 4 days of critical illness

1-pageSafe, 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 investigates the daily evolution of model-based insulin sensitivity level and variability for critical care patients receiving TGC during the first four days of their ICU stay

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

Performance of lung recruitment model in healthy anesthetised pigs

Patients with acute respiratory failure are given mechanical ventilation (MV) for treatment and breathing support. During MV, positive end-expiratory pressure (PEEP) is applied to recruit collapsed alveoli and maximized oxygenation. However, there are no well-established methods for quantifying alveoli recruitment with PEEP increase

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