Blood glucose variability, measured as mean absolute glucose, strongly depends on the frequency of blood glucose level measurements

Multicenter Observational Study of the First-Generation Intravenous Blood Glucose Monitoring System in Hospitalized Patients

BACKGROUND

Current methods of blood glucose (BG) monitoring and insulin delivery are labor intensive and commonly fail to achieve the desired level of BG control. There is great clinical need in the hospital for a user-friendly bedside device that can automatically monitor the concentration of BG safely, accurately, frequently, and reliably.

METHODS

A 100-patient observation study was conducted at 6 US hospitals to evaluate the first generation of the Intravenous Blood Glucose (IVBG) System (Edwards Lifesciences LLC & Dexcom Inc). Device safety, accuracy, and reliability were assessed. A research nurse sampled blood from a vascular catheter every 4 hours for ≤ 72 hours and BG concentration was measured using the YSI 2300 STAT Plus Analyzer (YSI Life Sciences). The IVBG measurements were compared to YSI measurements to calculate point accuracy.

RESULTS

The IVBG systems logged more than 5500 hours of operation in 100 critical care patients without causing infection or inflammation of a vein. A total of 44135 IVBG measurements were performed in 100 patients with 30231 measurements from the subset of 75 patients used for accuracy analysis. In all, 996 IVBG measurements were time-matched with reference YSI measurements. These pairs had a mean absolute difference (MAD) of 11.61 mg/dl, a mean absolute relative difference (MARD) of 8.23%, 93% met 15/20% accuracy defined by International Organization for Standardization 15197:2003 standard, and 93.2% were in zone A of the Clarke error grid. The IVBG sensors were exposed to more than 200 different medications with no observable effect on accuracy.

CONCLUSIONS

The IVBG system is an automated and user-friendly glucose monitoring system that provides accurate and frequent BG measurements with great potential to improve the safety and efficacy of insulin therapy and BG control in the hospital, potentially leading to improved clinical outcomes.

Increased glycemic variability is independently associated with length of stay and mortality in noncritically ill hospitalized patients

OBJECTIVE

To investigate the association between glycemic variability (GV) and both length of stay (LOS) and 90-day mortality in noncritically ill hospitalized patients.

RESEARCH DESIGN AND METHODS

This study retrospectively analyzed 4,262 admissions to the general medicine or surgery services during a 2 year period. Patients with point-of-care glucose monitoring and a minimum of two glucose values per day on average were selected. GV was assessed by SD and coefficient of variation (CV). Data were analyzed with linear and logistic multivariate regression analysis in separate models for SD and CV. Analysis was performed with generalized estimating equations to adjust for correlation between multiple admissions in some individual cases.

RESULTS

After exclusions, 935 admissions comprised the sample. Results of adjusted analysis indicate that for every 10 mg/dL increase in SD and 10-percentage point increase in CV, LOS increased by 4.4 and 9.7%, respectively. Relative risk of death in 90 days also increased by 8% for every 10-mg/dL increase in SD. These associations were independent of age, race, service of care (medicine or surgery), previous diagnosis of diabetes, HbA1c, BMI, the use of regular insulin as a sole regimen, mean glucose, and hypoglycemia occurrence during the hospitalization.

CONCLUSIONS

Our results indicate that increased GV during hospitalization is independently associated with longer LOS and increased mortality in noncritically ill patients. Prospective studies with continuous glucose monitoring are necessary to investigate this association thoroughly and to generate therapeutic strategies targeted at decreasing GV.

Evaluation of the mean absolute glucose change as a measure of glycemic variability using continuous glucose monitoring data

BACKGROUND

The mean absolute glucose (MAG) change, originally developed to assess associations between glycemic variability (GV) and intensive care unit mortality, has not yet been validated. We used continuous glucose monitoring (CGM) datasets from patients with diabetes to assess the validity of MAG and to quantify associations with established measures of GV.

SUBJECTS AND METHODS

Validation was based on retrospective analysis of 72-h CGM data collected during clinical studies involving 815 outpatients (48 with type 1 diabetes and 767 with type 2 diabetes). Measures of GV included SD around the sensor glucose, interquartile range, mean amplitude of glycemic excursions, and the continuous overlapping net glycemic action indices at 1, 3, and 6 h. MAG was calculated using 5-min, 60-min, and seven-point glucose profile sampling intervals; correlations among the variability measures and effects of sampling frequency were assessed.

RESULTS

Strong linear correlations between MAG change and classical markers of GV were documented (r=0.587-0.809, P<0.001 for all), whereas correlations with both glycosylated hemoglobin and mean sensor glucose were found to be weak (r=0.246 and r=0.378, respectively). The magnitude of MAG change decreased in a nonlinear fashion (P<0.001), as intervals between glucose measurements increased. MAG change, as calculated from 5-min sensor glucose readings, did reflect relatively small differences in glucose fluctuations associated with glycemic treatment modality.

CONCLUSIONS

MAG change represents a valid GV index if closely spaced sensor glucose measurements are used, but does not provide any advantage over variability indices already used for assessing diabetes control.

Glycemic variability and glucose complexity in critically ill patients: a retrospective analysis of continuous glucose monitoring data

Introduction

Glycemic variability as a marker of endogenous and exogenous factors, and glucose complexity as a marker of endogenous glucose regulation are independent predictors of mortality in critically ill patients. We evaluated the impact of real time continuous glucose monitoring (CGM) on glycemic variability in critically ill patients on intensive insulin therapy (IIT), and investigated glucose complexity - calculated using detrended fluctuation analysis (DFA) - in ICU survivors and non-survivors.

Methods

Retrospective analysis were conducted of two prospective, randomized, controlled trials in which 174 critically ill patients either received IIT according to a real-time CGM system (n = 63) or according to an algorithm (n = 111) guided by selective arterial blood glucose measurements with simultaneously blinded CGM for 72 hours. Standard deviation, glucose lability index and mean daily delta glucose as markers of glycemic variability, as well as glucose complexity and mean glucose were calculated.

Results

Glycemic variability measures were comparable between the real time CGM group (n = 63) and the controls (n = 111). Glucose complexity was significantly lower (higher DFA) in ICU non-survivors (n = 36) compared to survivors (n = 138) (DFA: 1.61 (1.46 to 1.68) versus 1.52 (1.44 to 1.58); P = 0.003). Diabetes mellitus was significantly associated with a loss of complexity (diabetic (n = 33) versus non-diabetic patients (n = 141) (DFA: 1.58 (1.48 to 1.65) versus 1.53 (1.44 to 1.59); P = 0.01).

Conclusions

IIT guided by real time CGM did not result in significantly reduced glycemic variability. Loss of glucose complexity was significantly associated with mortality and with the presence of diabetes mellitus.