Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance

BACKGROUND

Critically ill ICU patients frequently experience acute insulin resistance and increased endogenous glucose production, manifesting as stress-induced hyperglycemia and hyperinsulinemia. STAR (Stochastic TARgeted) is a glycemic control protocol, which directly manages inter- and intra- patient variability using model-based insulin sensitivity (SI). The model behind STAR assumes a population constant for endogenous glucose production (EGP), which is not otherwise identifiable.

OBJECTIVE

This study analyses the effect of estimating EGP for ICU patients with very low SI (severe insulin resistance) and its impact on identified, model-based insulin sensitivity identification, modeling accuracy, and model-based glycemic clinical control.

METHODS

Using clinical data from 717 STAR patients in 3 independent cohorts (Hungary, New Zealand, and Malaysia), insulin sensitivity, time of insulin resistance, and EGP values are analyzed. A method is presented to estimate EGP in the presence of non-physiologically low SI. Performance is assessed via model accuracy.

RESULTS

Results show 22%-62% of patients experience 1+ episodes of severe insulin resistance, representing 0.87%-9.00% of hours. Episodes primarily occur in the first 24 h, matching clinical expectations. The Malaysian cohort is most affected. In this subset of hours, constant model-based EGP values can bias identified SI and increase blood glucose (BG) fitting error. Using the EGP estimation method presented in these constrained hours significantly reduced BG fitting errors.

CONCLUSIONS

Patients early in ICU stay may have significantly increased EGP. Increasing modeled EGP in model-based glycemic control can improve control accuracy in these hours. The results provide new insight into the frequency and level of significantly increased EGP in critical illness.

Reconstructing asynchrony for mechanical ventilation using a hysteresis loop virtual patient model

BACKGROUND

Patient-specific lung mechanics during mechanical ventilation (MV) can be identified from measured waveforms of fully ventilated, sedated patients. However, asynchrony due to spontaneous breathing (SB) effort can be common, altering these waveforms and reducing the accuracy of identified, model-based, and patient-specific lung mechanics.

METHODS

Changes in patient-specific lung elastance over a pressure-volume (PV) loop, identified using hysteresis loop analysis (HLA), are used to detect the occurrence of asynchrony and identify its type and pattern. The identified HLA parameters are then combined with a nonlinear mechanics hysteresis loop model (HLM) to extract and reconstruct ventilated waveforms unaffected by asynchronous breaths. Asynchrony magnitude can then be quantified using an energy-dissipation metric, Easyn, comparing PV loop area between model-reconstructed and original, altered asynchronous breathing cycles. Performance is evaluated using both test-lung experimental data with a known ground truth and clinical data from four patients with varying levels of asynchrony.

RESULTS

Root mean square errors for reconstructed PV loops are within 5% for test-lung experimental data, and 10% for over 90% of clinical data. Easyn clearly matches known asynchrony magnitude for experimental data with RMS errors < 4.1%. Clinical data performance shows 57% breaths having Easyn > 50% for Patient 1 and 13% for Patient 2. Patient 3 only presents 20% breaths with Easyn > 10%. Patient 4 has Easyn = 0 for 96% breaths showing accuracy in a case without asynchrony.

CONCLUSIONS

Experimental test-lung validation demonstrates the method's reconstruction accuracy and generality in controlled scenarios. Clinical validation matches direct observations of asynchrony in incidence and quantifies magnitude, including cases without asynchrony, validating its robustness and potential efficacy as a clinical real-time asynchrony monitoring tool.

Model-based PEEP titration versus standard practice in mechanical ventilation: a randomised controlled trial

Background

Positive end-expiratory pressure (PEEP) at minimum respiratory elastance during mechanical ventilation (MV) in patients with acute respiratory distress syndrome (ARDS) may improve patient care and outcome. The Clinical utilisation of respiratory elastance (CURE) trial is a two-arm, randomised controlled trial (RCT) investigating the performance of PEEP selected at an objective, model-based minimal respiratory system elastance in patients with ARDS.

Methods and design

The CURE RCT compares two groups of patients requiring invasive MV with a partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio ≤ 200; one criterion of the Berlin consensus definition of moderate (≤ 200) or severe (≤ 100) ARDS. All patients are ventilated using pressure controlled (bi-level) ventilation with tidal volume = 6–8 ml/kg. Patients randomised to the control group will have PEEP selected per standard practice (SPV). Patients randomised to the intervention will have PEEP selected based on a minimal elastance using a model-based computerised method. The CURE RCT is a single-centre trial in the intensive care unit (ICU) of Christchurch hospital, New Zealand, with a target sample size of 320 patients over a maximum of 3 years. The primary outcome is the area under the curve (AUC) ratio of arterial blood oxygenation to the fraction of inspired oxygen over time. Secondary outcomes include length of time of MV, ventilator-free days (VFD) up to 28 days, ICU and hospital length of stay, AUC of oxygen saturation (SpO₂)/FiO₂ during MV, number of desaturation events (SpO₂ < 88%), changes in respiratory mechanics and chest x-ray index scores, rescue therapies (prone positioning, nitric oxide use, extracorporeal membrane oxygenation) and hospital and 90-day mortality.

Discussion

The CURE RCT is the first trial comparing significant clinical outcomes in patients with ARDS in whom PEEP is selected at minimum elastance using an objective model-based method able to quantify and consider both inter-patient and intra-patient variability. CURE aims to demonstrate the hypothesized benefit of patient-specific PEEP and attest to the significance of real-time monitoring and decision-support for MV in the critical care environment.

Trial registration

Australian New Zealand Clinical Trial Registry, ACTRN12614001069640. Registered on 22 September 2014.

(https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366838&isReview=true) The CURE RCT clinical protocol and data usage has been granted by the New Zealand South Regional Ethics Committee (Reference number: 14/STH/132).

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

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.

Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care

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 h 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.

Pilot study of the SPRINT glycemic control protocol in a Hungarian medical intensive care unit

INTRODUCTION

Stress-induced hyperglycemia increases morbidity and mortality. Tight control can reduce mortality but has proven difficult to achieve. The SPRINT (Specialized Relative Insulin and Nutrition Tables) protocol is the only protocol that reduced both mortality and hypoglycemia by modulating both insulin and nutrition, but it has not been tested in independent hospitals.

METHODS

SPRINT was used for 12 adult intensive care unit patients (949 h) at Kálmán Pándy Hospital (Gyula, Hungary) as a clinical practice assessment. Insulin recommendations (0-6 U/h) were administered via constant infusion rather than bolus delivery. Nutrition was administered per local standard protocol, weaning parenteral to enteral nutrition, but was modulated per SPRINT recommendations. Measurement was every 1 to 2 h, per protocol. Glycemic performance is assessed by percentage of blood glucose (BG) measurements in glycemic bands for the cohort and per patient. Safety from hypoglycemia is assessed by numbers of patients with BG < 2.2 (severe) and %BG < 3.0 and < 4.0 mmol/liter (moderate and light). Clinical effort is assessed by measurements per day. Results are median (interquartile range).

RESULTS

There were 742 measurements over 1088 h of control (16.4 measurements/day), which is similar to clinical SPRINT results (16.2/day). Per-patient hours of control were 65 (50-95) h. Initial per-patient BG was 10.5 (7.9-11.2) mmol/liter. All patients (100%) reached 6.1 mmol/liter. Cohort BG was 6.3 (5.5-7.5) mmol/liter, with 42.2%, 65.1% and 77.6% of BG in the 4.0-6.1, 4.0-7.0, and 4.0-8.0 mmol/liter bands. Per-patient, median percentage time in these bands was 40.2 (26.7-51.5)%, 62.5 (46.0-75.7)%, and 74.7 (61.6.8-87.8)%, respectively. No patients had BG < 2.2 mmol/liter, and the %BG < 4.0 mmol/liter was 1.9%. These results were achieved using 3.0 (3.0-5.0) U/h of insulin with 7.4 (4.4-10.2) g/h of dextrose administration (all sources) for the cohort. Per-patient median insulin administration was 3.0 (3.0-3.0) U/h and 7.1 (3.4-9.6) g/h dextrose. Higher carbohydrate nutrition formulas than were used in SPRINT are offset by slightly higher insulin administration in this study.

CONCLUSIONS

The glycemic performance shows that using the SPRINT protocol to guide insulin infusions and nutrition administration provided very good glycemic control in initial pilot testing, with no severe hypoglycemia. The overall design of the protocol was able to be generalized with good compliance and outcomes across geographically distinct clinical units, patients, and clinical practice.

Differences in the laboratory parameters of obese and healthy Hungarian children and their use in automatic classification

Obesity is a rapidly spreading endemic in almost every country of the developed world, of which Hungary is no exception. By a joint research project we aim to deepen our understanding of obesity-associated, and especially obesity-predicting changes of clinical markers (anthropometric indices, body composition, laboratory results etc.) in children, especially in teenage population. This paper presents the preliminary results of our investigations which pertain to obesity-related alterations in routine blood test parameters. For that end, we examined 340 healthy and obese children. Results show that there are differences between the routine laboratory parameters of obese and healthy subjects that are both statistically significant and medically interesting. We point out these differences in a statistically precise way, and show a method which can be efficiently used to classify children based on their laboratory parameters. This result can be used later to develop a more realistic model to predict the risk of obesity.

Stery-hand: A new device to support hand disinfection

Incomplete disinfection can cause serious complications in surgical care. The teaching of effective hand washing is crucial in modern medical training. To support the objective evaluation of hand disinfection, we developed a compact, mobile device, relying on digital imaging and image processing. The hardware consists of a metal case with matte black interior, ultra-violet lighting and a digital camera. Image segmentation and clustering are performed on a regular notebook. The hand washing procedures performed with a soap mixed with UV-reflective powder. This results the skin showing bright under UV light only on the treated (sterile) surfaces. When the surgeon inserts its hands into the box, the camera placed on the top takes an image of the hand for evaluation. The software performs the segmentation and clustering automatically. First, the hand contour is determined from the green intensity channel of the recorded RGB image. Then, the pixels of the green channel belonging to the hand are partitioned to three clusters using a quick, histogram based fuzzy c-means algorithm. The optimal threshold between the intensities of clean and dirty areas is extracted using these clusters, while the final approximated percentage of the clean area is computed using a weighting formula. The main advantage of our device is the ability to obtain objective and comparable result on the quality of hand disinfection. It may find its best use in the clinical education and training.

Stochastic approach to error estimation for image-guided robotic systems

Image-guided surgical systems and surgical robots are primarily developed to provide patient safety through increased precision and minimal invasiveness. Even more, robotic devices should allow for refined treatments that are not possible by other means. It is crucial to determine the accuracy of a system, to define the expected overall task execution error. A major step toward this aim is to quantitatively analyze the effect of registration and tracking-series of multiplication of erroneous homogeneous transformations. First, the currently used models and algorithms are introduced along with their limitations, and a new, probability distribution based method is described. The new approach has several advantages, as it was demonstrated in our simulations. Primarily, it determines the full 6 degree of freedom accuracy of the point of interest, allowing for the more accurate use of advanced application-oriented concepts, such as Virtual Fixtures. On the other hand, it becomes feasible to consider different surgical scenarios with varying weighting factors.

Detection of the root canal's centerline from dental micro-CT records

This paper presents a novel image processing procedure dedicated to the automated detection of the medial axis of the root canal from dental micro CT records. The 3D model of root canal is built up from several hundreds of parallel cross sections, using image enhancement and segmentation, center point detection in the segmented slice, three dimensional inner surface reconstruction and morphological skeleton extraction in three dimensions. The central line of the root canal is interpolated as a 3D spline curve. The proposed procedure can help prepare several kinds of endodontic interventions.

Codes in the codons: construction of a codon/amino acid periodic table and a study of the nature of specific nucleic acid-protein interactions

The theory of "codon-amino acid coevolution" was first proposed by Woese in 1967. It suggests that there is a stereochemical matching - that is, affinity - between amino acids and certain of the base triplet sequences that code for those amino acids. We have constructed a common periodic table of codons and amino acids, where the nucleic acid table showed perfect axial symmetry for codons and the corresponding amino acid table also displayed periodicity regarding the biochemical properties (charge and hydrophobicity) of the 20 amino acids and the position of the stop signals. The table indicates that the middle (2/sup nd/) amino acid in the codon has a prominent role in determining some of the structural features of the amino acids. The possibility that physical contact between codons and amino acids might exist was tested on restriction enzymes. Many recognition site-like sequences were found in the coding sequences of these enzymes and as many as 73 examples of codon-amino acid co-location were observed in the 7 known 3D structures (December 2003) of endonuclease-nucleic acid complexes. These results indicate that the smallest possible units of specific nucleic acid-protein interaction are indeed the stereochemically compatible codons and amino acids.

Filtering and contrast enhancement on subtracted direct digital angiograms

This work presents the results of a research related to medical image subtraction algorithms. The selected area is of direct digital X-ray angiography, where subtraction algorithms are the basis of most acquisition and reviewing protocols. The goal of this research is to analyze the currently existing image subtraction algorithms and to propose a new approach based on the experienced limitations, respectively to develop a new imaging technique that allows both contrast agent and radiation dose reduction. The enhancement of the subtraction algorithms is targeted by two means: a) noise reduction on image frames, b) identification of contrast agent injected regions. Both aspects will be studied based on the analysis of the spatio-temporal signal variation that image pixel intensities represent, therefore the resulting algorithm can not be used real time during image acquisition, but as a post processing technique during review. The temporal variation of pixel intensities was then analyzed and a patter check was followed to identify pixels being part of a contrast agent injected region. This information was used to highlight regions of interest and to increase the contrast in poorly injected areas.