Technology to treat hyperglycemia in trauma

Elevation of White Blood Cell Subtypes in Adult Trauma Patients with Stress-Induced Hyperglycemia

BACKGROUND

Blood immune cell subset alterations following trauma can indicate a patient's immune-inflammatory status. This research explored the influence of stress-induced hyperglycemia (SIH) on platelet counts and white blood cell (WBC) subtypes, including the derived indices of the monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), in trauma patients.

METHODS

We studied 15,480 adult trauma patients admitted from 1 January 1998 to 31 December 2022. They were categorized into four groups: nondiabetic normoglycemia (NDN, n = 11,602), diabetic normoglycemia (DN, n = 1750), SIH (n = 716), and diabetic hyperglycemia (DH, n = 1412). A propensity score-matched cohort was formed after adjusting for age, sex, and comorbidities, allowing for comparing the WBC subtypes and platelet counts.

RESULTS

Patients with SIH exhibited significantly increased counts of monocytes, neutrophils, and lymphocytes in contrast to NDN patients. However, no significant rise in platelet counts was noted in the SIH group. There were no observed increases in these cell counts in either the DN or DH groups.

CONCLUSIONS

Our results demonstrated that trauma patients with SIH showed significantly higher counts of monocytes, neutrophils, and lymphocytes when compared to NDN patients, whereas the DN and DH groups remained unaffected. This underscores the profound association between SIH and elevated levels of specific WBC subtypes.

Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

Minimizing the impact of time lag variability on accuracy evaluation of continuous glucose monitoring systems

BACKGROUND

Despite all commercially available continuous glucose monitoring (CGM) systems being designed to operate in the extracellular interstitial fluid, and even though there is a well-recognized time lag between the interstitial and the venous compartments, the accuracy of the CGM device readings is still evaluated against the glucose concentration in venous blood (VB) samples, thus resulting in a perceived decrease in accuracy. This article explains how different time lag compensation methods (no compensation, compensation with a fixed delay, compensation with a variable delay based on an intercompartmental diffusional model) have an impact on how CGM accuracy is evaluated.

METHODS

The data set used consisted of 210 CGM/blood glucose data pairs from 18 diabetes subjects (15 type 1 and 3 type 2) selected from a data base collected during two independent clinical trials. All CGM measurements were performed using the GlucoMen ®Day CGM system (A. Menarini Diagnostics, Italy), and the reference VB glucose measurements by means of a standard laboratory instrument. For each applied time lag compensation method, the CGM accuracy evaluation was performed as recommended by the POCT05-A consensus guideline.

RESULTS

The perceived accuracy of the CGM device significantly improved when applying both the fixed or the variable delay compensation method. However, it is worth noting how the variable delay method, which relies on a closer description of the intercompartmental diffusion processes, provided the best perception of the clinical accuracy of the device.

CONCLUSIONS

When assessing the accuracy of a CGM system, a crucial step in data analysis is to account for time lag, which enables minimization of the apparent decline in system accuracy.

Dosing accuracy with a novel pen device (SoloSTAR) as performed by patients with diabetes in a clinical setting

BACKGROUND

Pen devices can help to overcome some of the barriers associated with insulin therapy. The present study evaluated the accuracy of dose delivery by people with diabetes using the novel prefilled, disposable SoloSTAR device with insulin glargine (Lantus) and insulin glulisine (Apidra) (all from sanofi-aventis, Paris, France).

METHODS

People with type 1 or type 2 diabetes (insulin users or insulin naive) were eligible to participate in this randomized, single-center, open-label study. Each participant delivered six separate insulin doses into a sponge using SoloSTAR (three with glargine [10, 40, and 80 units] and three with glulisine [5, 15, and 30 units]). Pens were weighed before and after each test dose to determine the dose delivered. Thresholds for dosing accuracy were calculated according to the 2000 International Organization for Standardization (ISO) recommendations (Guideline 11608-1).

RESULTS

All doses of glargine and glulisine delivered (60 participants; 360 individual doses) were within the ISO limits. Mean (standard deviation) glargine doses delivered were 9.87 (0.24), 39.63 (0.36), and 79.02 (0.62) units for 10, 40, and 80 units, respectively. Insulin glulisine doses delivered were 4.98 (0.20), 14.87 (0.29), and 29.67 (0.34) units for 5, 15, and 30 units, respectively.

CONCLUSIONS

The SoloSTAR pen allows people with diabetes to achieve a dosing accuracy with glargine and glulisine similar to that achieved in laboratory conditions. The dosing accuracy and ease of use of SoloSTAR may provide greater confidence in the precision and accuracy of the device while titrating glargine and/or glulisine to goal.

Analysis of algorithms for intensive care unit blood glucose control

Intensive care unit (ICU) blood glucose control algorithms were reviewed and analyzed in the context of linear systems theory and classical feedback control algorithms. Closed-loop performance was illustrated by applying the algorithms in simulation studies using an in silico model of an ICU patient. Steady-state and dynamic input-output analysis was used to provide insight about controller design and potential closed-loop performance. The proportional-integral-derivative, columnar insulin dosing (CID, Glucommander-like), and glucose regulation for intensive care patients (GRIP) algorithms were shown to have similar features and performance. The CID strategy is a time-varying proportional-only controller (no integral action), whereas the GRIP algorithm is a nonlinear controller with integral action. A minor modification to the GRIP algorithm was suggested to improve the closed-loop performance. Recommendations were made to guide control theorists on important ICU control topics worthy of further study.

Convergence of continuous glucose monitoring and in-hospital tight glycemic control: closing the gap between caregivers and industry

The convergence of continuous glucose monitoring (CGM) and tight glycemic control protocols is approaching. As with the diffusion of any innovative technology, there will be challenges that will likely delay widespread adoption. With the objective of assessing the current mindset of health care professionals toward CGM adoption in the hospital intensive care unit (ICU) setting and resulting implications to industry, Boston Biomedical Consultants surveyed >60 U.S. ICU managers and nurses during Spring 2007. The underlying sentiment expressed by survey respondents toward CGM was positive, with many citing potential benefits of CGM adoption, such as labor savings, improved glycemic control, and assistance with insulin dosing. While the demand for CGM in the hospital clearly exists, early stage product acceptance will remain limited given the substantial education, market development, and economic hurdles.

The need for continuous blood glucose monitoring in the intensive care unit

Insulin-based regimens decrease morbidity and mortality among critically ill patients by way of keeping glucose at tight control. Utilizing these regimens involves multiple measurements of glucose by way of finger pricking or through indwelling vascular catheters in order to adjust insulin doses. The limitations and risks of these methods of glucose monitoring are related to potential erroneous measurements, increased risk of infection, and a significant excess workload. An automated blood glucose monitoring device for glucose monitoring of critically ill patients is needed to improve patient care while avoiding the disadvantages of currently used glucose monitoring methodologies.