Hematocrit compensation in electrochemical blood glucose monitoring systems

Background

Hematocrit (Hct) is a common interferent in test strips used by diabetes patients to self-monitor blood glucose (BG), resulting in measurement bias. Described is an electrochemical BG monitoring system (OneTouch^® Verio™) that uses a cofacial sensor design, soluble enzyme chemistry, and multiphasic waveform to effectively correct for patient Hct, delivering an accurate reading for whole BG.

Methods

The test strip comprises thin-film gold and palladium electrodes arranged cofacially and spatially separated with a thin spacer. Soluble glucose-sensing reagents are located on the lower palladium electrode and are hydrated on sample application. Blood glucose is oxidized by flavoprotein glucose dehydrogenase, with electron transfer via (reduced) potassium ferrocyanide mediator at the palladium electrode. Hematocrit levels are estimated by measuring oxidation of mediator diffusion to the upper gold electrode during the first portion of the assay. The Hct-corrected glucose levels are determined by an on-meter algorithm.

Results

In performance testing of blood samples at five glucose levels (30–560 mg/dl) and five Hct levels (19–61%), using 12 test meters and 3 test strip lots, 100% of results (N = 2700) met International Organization for Standardization accuracy criteria (within ± 15 mg/dl and ± 20% of reference results at glucose levels of <75 and ≥75 mg/dl, respectively). Furthermore, 99.9% (2698 of 2700) of results were within ±12 mg/dl and ± 15% of reference values at glucose levels <80 and ≥80 mg/dl, respectively.

Conclusions

The technology used in this system provides accurate BG measurements that are insensitive to Hct levels across the range 20–60%.     

Retrospective Outcomes of Glucose Control in Critically Ill Children

Background

Hyperglycemia is a significant problem for critically ill children. Treatment for hyperglycemia remains controversial. This study explores the effect of controlling blood glucose (BG) in hyperglycemic critically ill children.

Methods

A retrospective cohort of nondiabetic critically ill children (defined as requiring mechanical ventilation and/or vasopressors) with BG persistently ≥150 mg/dl and treated with insulin (treatment group) were compared with a historical cohort of similar children who did not receive interventions to control hyperglycemia (baseline group).

Results

There were 130 children in the treatment group and 137 children in the baseline group. Mean BG in the treatment group was 140 ± 24 mg/dl compared with 179 ± 47 mg/dl in the baseline group (p < .001). After adjusting for patient characteristics, cointerventions, and glucose metrics, patients in the treatment group had 2.5 fewer intensive care unit (ICU)-free days (i.e., number of days alive and discharged from ICU within 28 days after inclusion) than the baseline group (p = .023). Glucose control was not independently associated with duration of ICU stay, ventilator-free days, vasopressor-free days, or mortality.

Conclusions

Blood glucose control appears associated with worse outcomes in critically ill children. Our data combined with conflicting results in adults leads us to strongly advocate for the conduct of randomized trials on glucose control in critically ill children.     

Concealed Maternal Blood Glucose Excursions Correlate with Birth Weight Centile

Background

The objective of this study was to test the hypothesis that maternal blood glucose excursions correlate with deviation from optimized birth weight.

Methods

Patients were recruited for 3-day continuous glucose monitoring (CGM) plus self-blood glucose monitoring followed by routine diabetes screening at 26-28 weeks gestation. Patients and caregivers were blinded to CGM results. The magnitude and duration of blood glucose (BG) excursions were measured as a “glycemia index.” A customized birth weight centile was calculated.

Results

Twenty-three patients consented, 21 completed the study: 5 diabetic and 16 nondiabetic individuals. The duration of CGM was 72 (±7.2) hours, and each patient performed self-BG monitoring ≥3 times per day. All diabetic and 10 nondiabetic patients had several measured BG excursions above 130 mg/dl. A positive correlation was observed between birth weight centile and glycemia index above 130 (p < 0.03); the trend persisted for nondiabetic patients alone (p < 0.05). No significant correlation was noted between birth weight centile and average 3-day CGM values, 3-day fasting BG, average 3-day self-BG monitoring values, or diabetes screening BG value.

Conclusions

The glycemia index has a better correlation with birth weight centile than BG measured by conventional methods in a mixed diabetic and nondiabetic population. Fetal exposure to maternal blood glucose excursions correlates positively with fetal growth, even in nondiabetic patients with apparently normal glucose tolerance.     

Technology for Hospital Management of Diabetes: Blood Glucose Measurements in Arterial Blood of Intensive Care Unit Patients Submitted to Tight Glycemic Control: Agreement between Bedside Tests

Background

Implementing tight glycemic control (TGC) in intensive care unit (ICU) patients requires accurate blood glucose (BG) monitoring. We evaluated the performance of two commercially available bedside glucometers, Accu-Chek^® and HemoCue^®, in patients admitted to the ICU and in whom TGC was applied.

Methods

Thirty-seven adult ICU patients were prospectively included. During 48 hours, BG was determined simultaneously on the same arterial blood sample using the two point-of-care testing (POCT) glucometers as compared with the standard technique. Data of 452 paired measurements were analyzed using linear regression, Clark error grid analysis (EGA), the method of Bland–Altman, and the GLYCENSIT procedure.

Results

Both tested glucometers showed satisfactory results when evaluated with linear regression and EGA. Correlation coefficients were above 0.9, and 100% of all the glucose readings were within the safe zones A and B using EGA. However, when applying more appropriate tests, both sensors failed to provide sufficient accuracy in the setting of TGC in ICU patients. The Hemocue revealed a bias of >10 mg/dl with a trend to systematically overestimate the actual BG value. The bias for the Accu-Chek was 6 mg/dl with wide limits of agreement and a variable over- and underestimation of the actual BG value depending on the level of BG (hypo-, normo-, or hyperglycemia).

Conclusions

When TGC is implemented in ICU practice, caution is warranted when adjusting insulin rates based only on BG readings obtained by the tested glucometers. ICU practitioners should weigh the advantages and disadvantages of such devices: a greater bias but with a more predictable error and measurement behavior versus a somewhat lower bias but with an unpredictable direction of the difference.     

Perioperative hyperglycemia and postoperative infection after lower limb arthroplasty

Background

One of the most serious complications after major orthopedic surgery is deep wound or periprosthetic joint infection. Various risk factors for infection after hip and knee replacement surgery have been reported, including patients'' comorbidities and surgical technique factors. We investigated whether hyperglycemia and diabetes mellitus (DM) are associated with infection that requires surgical intervention after total hip and knee arthroplasty.

Methods

We reviewed our computerized database for elective primary total hip and knee arthroplasty from 2000 to 2008. Demographic information, past medical history of patients, perioperative biochemistry, and postoperative complications were reviewed.Patients were divided into two groups: infected group (101 patients who had surgical intervention for infection at our institution within 2 years after primary surgery) and noninfected group (1847 patients with no intervention with a minimum of one year follow-up. The data were analyzed using t, chi-squared, and Fisher''s exact tests.

Results

There were significantly more diabetes patients in the infected group compared with the noninfected group (22% versus 9%, p < .001). Infected patients had significantly higher perioperative blood glucose (BG) values: preoperative BG (112 ± 36 versus 105 ± 31 mg/dl, p = .043) and postoperative day (POD) 1 BG (154 ± 37 versus 138 ± 31 mg/dl, p < .001). Postoperative morning hyperglycemia (BG >200 mg/dl) increased the risk for the infection more than two-fold. Non-DM patients were three times more likely to develop the infection if their morning BG was >140 mg/dl on POD 1, p = .001. Male gender, higher body mass index, knee arthroplasty, longer operative time and hospital stay, higher comorbidity index, history of myocardial infarction, congestive heart failure, and renal insufficiency were also associated with the infection.

Conclusions

Diabetes mellitus and morning postoperative hyperglycemia were predictors for postoperative infection following total joint arthroplasty. Even patients without a diagnosis of DM who developed postoperative hyperglycemia had a significantly increased risk for the infection.     

Failure to Control Hyperglycemia in NonCritically Ill Diabetes Patients Despite Standard Glycemic Management in a Hospital Setting

Background

Successful control of hyperglycemia has been shown to improve outcomes for diabetes patients in a clinical setting. We assessed the quality of physician-based glycemic management in two general wards, considering the most recent recommendations for glycemic control for noncritically ill patients (<140 mg/dl for premeal glucose).

Methods

Quality of glycemic management of 50 patients in two wards (endocrinology, cardiology) was assessed retrospectively by analyzing blood glucose (BG) levels, the glycemic management effort, and the online questionnaire.

Results

Glycemic control was clearly above the recommended target (mean BG levels: endocrinology: 175 ± 62 mg/dl; cardiology: 186 ± 68 mg/dl). When comparing the first half with the second half of the hospital stay, we found no difference in glycemic control (endocrinology: 168 ± 32 vs 164 ± 42 mg/dl, P = .67; cardiology: 174 ± 36 mg/dl vs 170 ± 42 mg/dl, P =.51) and in insulin dose (endocrinology: 15 ± 14 IU vs 15 ± 13 IU per day, P = .87; cardiology: 27 ± 17 IU vs 27 ± 18 IU per day, P = .92), despite frequent BG measurements (endocrinology: 2.7 per day; cardiology: 3.2 per day). A lack of clearly defined BG targets was indicated in the questionnaire.

Conclusions

The recommended BG target range was not achieved in both wards. Analysis of routine glycemic management demonstrated considerable glycemic management effort, but also a lack of translation into adequate insulin therapy. Implementation of corrective measures, such as structured treatment protocols, is essential.     

Continuous Glucose Monitoring System in a Rural Intensive Care Unit: A Pilot Study Evaluating Accuracy and Acceptance

Background

Glucose management in an intensive care unit (ICU) is labor-intensive. A continuous glucose monitoring system (CGMS) has the potential to improve efficiency and safety in this setting. The goal of this study was to determine if the Medtronic Guardian^® REAL-Time CGMS was accurate and tolerated by patients in a rural hospital ICU unit.

Method

Differences between individual finger stick blood glucose (FSBG) and CGMS values were compared to American Diabetes Association (ADA) and International Organization for Standardization (ISO) standards. Continuous glucose monitoring system accuracy was evaluated over four ranges: <75, 75–140, 140–200, and >200 mg/dl. Other accuracy measures [mean absolute deviation (MAD), mean absolute relative difference (MARD), and coefficient of linear regression of CGMS on FSBG] were calculated. Nursing staff and patients were surveyed regarding use of the CGMS in the ICU.

Results

Twenty-nine participants had 320 FSBG and corresponding CGMS readings. Sixty-two percent of participants were admitted with diabetic ketoacidosis (DKA). Two hundred and thirteen (66.6%) were accurate within the ISO standard, whereas only 70 out of 320 (21.9%) were within the 5% ADA standard. The CGMS was most accurate in euglycemia. Technical difficulties, such as adequate time for “wetting” and calibration of electrodes, arose with the sensors. The MAD was 28.3 mg/dl, the MRAD was 17.4%, and the linear regression coefficient of CGMS on FSBG was 0.834 (p < 0.001).

Conclusions

The CGMS is well tolerated by ICU patients but, at present, is not sufficiently accurate to be used for therapeutic decisions in the acute setting, particularly in patients with diabetic ketoacidosis. There is a need to find resolution to the technical issues regarding electrode “wetting” and calibration if CGMS use in the ICU setting is to provide an effective means of diabetes care and management.     

Technology for Hospital Management of Diabetes: Evaluation of Implementation of a Fully Automated Algorithm (Enhanced Model Predictive Control) in an Interacting Infusion Pump System for Establishment of Tight Glycemic Control in Medical Intensive Care Unit Patients

Background

The objective of this study was to investigate the performance of a newly developed decision support system for the establishment of tight glycemic control in medical intensive care unit (ICU) patients for a period of 72 hours.

Methods

This was a single-center, open, non-controlled feasibility trial including 10 mechanically ventilated ICU patients. The CS-1 decision support system (interacting infusion pumps with integrated enhanced model predictive control algorithm and user interface) was used to adjust the infusion rate of administered insulin to normalize blood glucose. Efficacy and safety were assessed by calculating the percentage of values within the target range (80–110 mg/dl), hyperglycemic index, mean glucose, and hypoglycemic episodes (<40 mg/dl).

Results

The percentage of values in time in target was 47.0% (±13.0). The average blood glucose concentration and hyperglycemic index were 109 mg/dl (±13) and 10 mg/dl (±9), respectively. No hypoglycemic episode (<40 mg/dl) was detected. Eleven times (1.5% of all given advice) the nurses did not follow and, thus, overruled the advice of the CS-1 system. Several technical malfunctions of the device (repetitive error messages and missing data in the data log) due to communication problems between the new hardware components are shortcomings of the present version of the device. As a consequence of these technical failures of system integration, treatment had to be stopped ahead of schedule in three patients.

Conclusions

Despite technical malfunctions, the performance of this prototype CS-1 decision support system was, from a clinical point of view, already effective in maintaining tight glycemic control. Accordingly, and with technical improvement required, the CS-1 system has the capacity to serve as a reliable tool for routine establishment of glycemic control in ICU patients.     

Benchmarking glucose results through automation: the 2009 Remote Automated Laboratory System Report

Background

Hyperglycemia in the adult inpatient population remains a topic of intense study in U.S. hospitals. Most hospitals have established glycemic control programs but are unable to determine their impact. The 2009 Remote Automated Laboratory System (RALS) Report provides trends in glycemic control over 4 years to 576 U.S. hospitals to support their effort to manage inpatient hyperglycemia.

Methods

A proprietary software application feeds de-identified patient point-of-care blood glucose (POC-BG) data from the Medical Automation Systems RALS-Plus data management system to a central server. Analyses include the number of tests and the mean and median BG results for intensive care unit (ICU), non-ICU, and each hospital compared to the aggregate of the other hospitals.

Results

More than 175 million BG results were extracted from 2006–2009; 25% were from the ICU. Mean range of BG results for all inpatients in 2006, 2007, 2008, and 2009 was 142.2–201.9, 145.6–201.2, 140.6–205.7, and 140.7–202.4 mg/dl, respectively. The range for ICU patients was 128–226.5, 119.5–219.8, 121.6–226.0, and 121.1–217 mg/dl, respectively. The range for non-ICU patients was 143.4–195.5, 148.6–199.8, 145.2–201.9, and 140.7–203.6 mg/dl, respectively. Hyperglycemia rates of >180 mg/dl in 2008 and 2009 were examined, and hypoglycemia rates of <40 mg/dl (severe) and <70 mg/dl (moderate) in both 2008 and 2009 were calculated.

Conclusions

From these data, hospitals can determine the current state of glycemic control in their hospital and in comparison to other hospitals. For many, glycemic control has improved. Automated POC-BG data management software can assist in this effort.     

Evaluation of Point-of-Care Blood Glucose Measurements in Patients with Diabetic Ketoacidosis or Hyperglycemic Hyperosmolar Syndrome Admitted to a Critical Care Unit

Background

Point-of-care (POC) blood glucose (BG) measurement is currently not recommended in the treatment of patients presenting with diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar syndrome (HHS).

Methods

We prospectively evaluated and compared capillary and venous POC BG values with laboratory venous glucose in patients with DKA or HHS admitted to one critical care unit over 8 months.

Results

Venous laboratory glucose was strongly correlated with venous (r = 0.98) and capillary (r = 0.96) POC glucose values, though POC glucose values were higher than venous laboratory values (venous POC 21 ± 3 mg/dl, capillary POC 30 ± 4 mg/dl; both p < .001). Increased plasma osmolality had no effect on glucose meter error, while acidemia (pH < 7.3) was associated with greater glucose meter error (p = .04) independent of glucose levels. Comparing hypothetical insulin infusion rates based on laboratory venous glucose to actual infusion rates based on POC glucose values showed that 33/61 insulin infusion rates would have been unchanged, while 28 out of 61 rates were on average 7% ± 2% higher. There were no instances of hypoglycemia in any of the patients.

Conclusions

Overall, both venous and capillary POC BG values were safe for the purpose of titrating insulin infusions in patients with severe hyperglycemia. Acidemia, but not hyperosmolality, increased POC BG value errors.     

Intraoperative accuracy of a point-of-care glucose meter compared with simultaneous central laboratory measurements

Background

Concerns have been raised about the use of point-of-care (POC) glucose meters in the hospital setting.Accuracy has been questioned especially in critically ill patients. Although commonly used in intensive care units and operating rooms, POC meters were not approved by the Food and Drug Administration for such use.Data on POC glucose meter performance during anesthesia are lacking. We evaluated accuracy of a POC meter in the intraoperative setting.

Methods

We retrospectively reviewed 4,333 intraoperative records in which at least one intraoperative glucose was measured using electronic medical records at a large academic hospital. We evaluated the accuracy of a POC glucose meter (ACCU-CHEK® Inform, Roche Pharmaceuticals) based on the 176 simultaneous central laboratory (CL) blood glucose (BG) measurements that were found (i.e., documented collection times within 5 minutes). Point-of-care and central lab BG differences were analyzed by Bland-Altman and revised error grid analysis (rEGA).

Results

Mean POC BG was 163.4 ± 64.7 mg/dl [minimum (min) 48 mg/dl, maximum (max) 537 mg/dl] and mean CL BG was 162.6 ± 65.1 mg/dl (min 44 mg/dl, max 502 mg/dl). Mean absolute difference between POC and CL BG was24.3 mg/dl. Mean absolute relative difference was 16.5% with standard deviation 26.4%. Point-of-care measurements showed a bias of 0.8 relative to the corresponding CL value, with a precision of 39.0 mg/dl. Forty (23%) POC BG values fell outside the Clinical and Laboratory Standards Institute guideline and 3.4% POC measurements fell in zones C and D of the rEGA plot.

Conclusions

The tested POC glucose meter performed poorly compared to a CL analyzer intraoperatively. Perioperative clinicians should be aware of limitations of specific POC glucose meters, and routine use of POC glucose meters as sole measurement devices in the intraoperative period should be carefully considered.     

Alarms for Continuous Glucose Monitors: Methods of Evaluating the Utility of Continuous Glucose Monitor Alerts

Background

The evaluation of continuous glucose monitor (CGM) alert performance should reflect patient use in real time. By evaluating alerts as real-time events, their ability to both detect and predict low and high blood glucose (BG) events can be examined.

Method

True alerts (TA) were defined as a CGM alert occurring within ± 30 minutes from the beginning of a low or a high BG event. The TA time to detection was calculated as [time of CGM alert] – [beginning of event]. False alerts (FA) were defined as a BG event outside of the alert zone within ± 30 minutes from a CGM alert. Analysis was performed comparing DexCom™ SEVEN^® PLUS CGM data to BG measured with a laboratory analyzer.

Results

Of 49 low glucose events (BG ≤70 mg/dl), with the CGM alert set to 90 mg/dl, the TA rate was 91.8%. For 50% of TAs, the CGM alert preceded the event by at least 21 minutes. The FA rate was 25.0%. Similar results were found for high alerts.

Conclusion

Continuous glucose monitor alerts are capable of both detecting and predicting low and high BG events. The setting of alerts entails a trade-off between predictive ability and FA rate. Realistic analysis of this trade-off will guide patients in the effective utilization of CGM.     

Accuracy of the CONTOUR® blood glucose monitoring system

Objective

The aim of the study was to assess the accuracy of the CONTOUR® blood glucose monitoring system (BGMS) according to the International Organization for Standardization''s International Standard 15197 (ISO 15197:2003) guidelines and to more stringent criteria.

Method

Finger stick blood samples from 105 subjects with diabetes (25 with type 1, 77 with type 2, and 3 with type unknown) were tested using the CONTOUR BGMS and YSI glucose analyzer.

Results

99.3% of results were within ISO 15197:2003 criteria (±15 mg/dl of YSI results at glucose concentrations <75 mg/dl and ±20% at glucose concentrations ≥75 mg/dl). Additionally, 96.7% of results were accurate according to more stringent criteria (±15 mg/dl of YSI results for glucose concentrations <100 mg/dl and ±15% for glucose concentrations ≥100 mg/dl). Error grid analysis showed that 99.3% and 0.7% of results were within zones A and B, respectively.

Conclusion

The CONTOUR BGMS exceeded both the minimum acceptable accuracy based on ISO 15197:2003 and the more stringent accuracy criteria.     

Hemoglobin A1c testing in an emergency department

Background

Emergency department (ED) visits for hyperglycemia are common and costly. Enhanced strategies for recognizing and managing patients with diabetes in the ED are needed. Hemoglobin A1c (A1C) testing is typically used to assess level of glycemic control in the 2–3 months preceding an office visit. In this article, we report on potential roles for point-of-care (POC) A1C testing in the ED for patients presenting with uncontrolled hyperglycemia.

Methods

We enrolled patients presenting to an urban tertiary care hospital ED with blood glucose (BG) ≥200 mg/dl who were otherwise stable for discharge (n = 86) in a prospective, nonrandomized pilot study. Antihyperglycemic medication management, survival-skills diabetes self-management education, and health system navigation were provided. Followup visits took place at 24–72 hours and at 2 and 4 weeks. Point-of-care A1C testing was performed at baseline and at 2 weeks. Baseline A1C results were used by the ED physician and the educator to inform the patient of likely preadmission glycemic classification, and the potential role that the (diabetes mellitus) DM medication regimen assigned in the ED had in enabling overall progress in glycemic control at 2 weeks post-ED initiation of treatment.

Results

At baseline, 50% of POC A1C values were >13%. Mean BG fell from 356 ± 110 mg/dl to 183 ± 103 mg/dl at 4 weeks (average decrease of 173.5 g/dl, p < 0.001). Mean A1C fell by 0.4%, from 12.0 ± 1.5% to 11.6 ± 1.6% at 2 weeks, p = 0.048. There were zero instances of day 1 hypoglycemia and overall hypoglycemia rates were low (1.3%).

Conclusions

Point-of-care A1C testing in the ED helped inform both the provider and the patient of likely prior glycemic status, including unrecognized or uncontrolled type 2 diabetes, and allowed emphasis of the importance of timely diabetes self-management education and medication management in preventing acute and chronic complications. Followup POC A1C testing at 2 weeks was used to confirm early improvement in glycemic control postintervention.     

Effect of short-term use of a continuous glucose monitoring system with a real-time glucose display and a low glucose alarm on incidence and duration of hypoglycemia in a home setting in type 1 diabetes mellitus

Background

The objective of this study was to examine whether setting the low glucose alarm of a Guardian^® REAL-Time continuous glucose monitoring system (CGMS) to 80 mg/dl for 3 days and providing instructions to users reduce the risk of hypoglycemia under free-living conditions in individuals with type 1 diabetes mellitus (T1DM).

Methods

Fourteen participants with T1DM aged 26.1 ± 6.0 years (mean ± standard deviation) were fitted with a CGMS and assigned for 3 days to either an alarm [low and high blood glucose (BG) alarms set at 80 and 200 mg/dl, respectively] or no alarm condition, with each treatment administered to all participants following a counterbalanced design. All participants were given detailed instructions on how to respond appropriately to low glucose alarms.

Results

The CGMS with alarm reduced the incidence of hypoglycemia (CGMS readings ≤65 mg/dl) by 44% as well as the time spent below this hypoglycemic threshold by 64% without increasing average BG levels. However, the CGMS with alarm had no effect on the incidence of symptomatic hypoglycemia.

Conclusions

Short-term use of the CGMS with alarm, together with appropriate instructions for users, reduces the incidence and duration of hypoglycemia, but only to a limited extent, in part because it overestimates BG in the low glucose range.     

Average daily risk range as a measure of glycemic risk is associated with mortality in the intensive care unit: a retrospective study in a burn intensive care unit

Background

Although tight glycemic control has been associated with improved outcomes in the intensive care unit (ICU), glycemic variability may be the influential factor in mortality. The main goal of the study was to relate blood glucose (BG) variability of burn ICU patients to outcomes using a sensitive measure of glycemic variability, the average daily risk range (ADRR).

Method

Data from patients admitted to a burn ICU were used. Patients were matched by total body surface area (TBSA) and injury severity score (ISS) to test whether increased BG variability measured by ADRR was associated with higher mortality risk and whether we could identify ADRR-based classifications associated with the degree of risk.

Results

Four ADRR classifications were identified: low risk, medium-low, medium-high, and high. Mortality progressively increased from 25% in the low-risk group to over 60% in the high-risk group (p < .001). In a post hoc analysis, age also contributed to outcome. Younger (age < 43 years) survivors and nonsurvivors matched by TBSA and ISS had no significant difference in age, mean BG or standard deviation of BG; however, nonsurvivors had higher ADRR (p < .01).

Conclusions

Independent of injury severity, glycemic variability measured by the ADRR was significantly associated with mortality in the ICU. When age was considered, ADRR was the only measure of glycemia significantly associated with mortality in younger patients with burns.     

Continuous Glucose Profiles in Healthy Subjects under Everyday Life Conditions and after Different Meals

Background

This study investigated continuous glucose profiles in nondiabetic subjects.

Methods

Continuous interstitial glucose measurement was performed under everyday life conditions (2 days) and after ingestion of four meals with standardized carbohydrate content (50 grams), but with different types of carbohydrates and variable protein and fat content. Twenty-four healthy volunteers (12 female, 12 male, age 27.1 ± 3.6 years) participated in the study. Each subject wore two microdialysis devices (SCGM1, Roche Diagnostics) simultaneously.

Results

The mean 24-hour interstitial glucose concentration under everyday life conditions was 89.3 ± 6.2 mg/dl (mean ± SD, n = 21), and mean interstitial glucose concentrations at daytime and during the night were 93.0 ± 7.0 and 81.8 ± 6.3 mg/dl, respectively. The highest postprandial glucose concentrations were observed after breakfast: 132.3 ± 16.7 mg/dl (range 101–168 mg/dl); peak concentrations after lunch and dinner were 118.2 ± 13.4 and 123.0 ± 16.9 mg/dl, respectively. Mean time to peak glucose concentration was between 46 and 50 minutes. After ingestion of standardized meals with fast absorption characteristics, peak interstitial glucose concentrations were 133.2 ± 14.4 and 137.2 ± 21.1 mg/dl, respectively. Meals with a higher fiber, protein, and fat content induced a smaller increase and a slower decrease of postprandial glucose concentrations with peak values of 99.2 ± 10.5 and 122.1 ± 20.4 mg/dl, respectively.

Conclusions

This study provided continuous glucose profiles in nondiabetic subjects and demonstrated that differences in meal composition are reflected in postprandial interstitial glucose concentrations. Regarding the increasing application of continuous glucose monitoring in diabetic patients, these data suggest that detailed information about the ingested meals is important for adequate interpretation of postprandial glucose profiles.     

Institutional Blood Glucose Monitoring System for Hospitalized Patients: An Integral Component of the Inpatient Glucose Control Program

Background

The ability to measure patient blood glucose levels at bedside in hospitalized patients and to transmit those values to a central database enables and facilitates glucose control and follow-up and is an integral component in the care of the hospitalized diabetic patient.

Objective

The goal of this study was to evaluate the performance of an institutional glucometer employed in the framework of the Program for the Treatment of the Hospitalized Diabetic Patient (PTHDP) at E. Wolfson Medical Center, Holon, Israel.

Methods

As part of the program to facilitate glucose control in hospitalized diabetic patients, an institutional glucometer was employed that permits uploading of data from stands located in each inpatient department and downloading of that data to a central hospital-wide database. Blood glucose values from hospitalized diabetic patients were collected from August 2007 to October 2008. The inpatient glucose control program was introduced gradually beginning January 2008.

Results

During the follow-up period, more than 150,000 blood glucose measures were taken. Mean glucose was 195.7 ± 99.12 mg/dl during the follow-up period. Blood glucose values declined from 206 ± 105 prior to PTHDP (August 2007–December 2007) to 186 ± 92 after its inception (January 2008–October 2008). The decline was associated significantly with time (r = 0.11, p < 0.0001). The prevalence of blood glucose values lower than 60 mg/dl was 1.48% [95% confidence interval (CI) 0.36%] prior to vs 1.55% (95% CI 0.37%) following implementation of the PTHDP. Concomitantly, a significant increase in the proportion of blood glucose values between 80 and 200 mg/dl was observed, from 55.5% prior to program initiation vs 61.6% after program initiation (p < 0.0001).

Conclusions

The present study was designed to observe changes in institution-wide glucose values following implementation of the PTHDP. Information was extracted from the glucometer system itself. Because the aforementioned study was not a clinical trial, we cannot rule out that factors other than introduction of the program could explain some of the variability observed. With these limitations in mind, it nevertheless appears that the PTHDP, of which the institutional glucometer is an integral, essential component, was associated with improved blood glucose values in the hospitalized diabetic patient.     

Effect of Insulin Feedback on Closed-Loop Glucose Control: A Crossover Study

Background

Closed-loop (CL) insulin delivery systems utilizing proportional-integral-derivative (PID) controllers have demonstrated susceptibility to late postprandial hypoglycemia because of delays between insulin delivery and blood glucose (BG) response. An insulin feedback (IFB) modification to the PID algorithm has been introduced to mitigate this risk. We examined the effect of IFB on CL BG control.

Methods

Using the Medtronic ePID CL system, four subjects were studied for 24 h on PID control and 24 h during a separate admission with the IFB modification (PID + IFB). Target glucose was 120 mg/dl; meals were served at 8:00 AM, 1:00 PM, and 6:00 PM and were identical for both admissions. No premeal manual boluses were given. Reference BG excursions, defined as incremental glucose rise from premeal to peak, and postprandial BG area under the curve (AUC; 0–5 h) were compared. Results are reported as mean ± standard deviation.

Results

The PID + IFB control resulted in higher mean BG levels compared with PID alone (153 ± 54 versus 133 ± 56 mg/dl; p < .0001). Postmeal BG excursions (114 ± 28 versus 114 ± 47 mg/dl) and AUCs (285 ± 102 versus 255 ± 129 mg/dl/h) were similar under both conditions. Total insulin delivery averaged 57 ± 20 U with PID versus 45 ± 13 U with PID + IFB (p = .18). Notably, eight hypoglycemic events (BG < 60 mg/dl) occurred during PID control versus none during PID + IFB.

Conclusions

Addition of IFB to the PID controller markedly reduced the occurrence of hypoglycemia without increasing meal-related glucose excursions. Higher average BG levels may be attributable to differences in the determination of system gain (Kp) in this study. The prevention of postprandial hypoglycemia suggests that the PID + IFB algorithm may allow for lower target glucose selection and improved overall glycemic control.     

Use of a continuous glucose sensor in an extracorporeal life support circuit

Background

Standard care for infants on extracorporeal life support (ECLS) relies on intermittent measurement of blood glucose (BG); however, this can lead to significant changes in BG that go unrecognized for several hours. The present study was designed to assess performance and clinical applicability of a subcutaneous glucose sensor technology modified for use as a blood-contacting sensor within the ECLS circuit.

Methods

Twelve children, aged 3 years or less, requiring ECLS support were studied. Three continuous glucose sensors (Medtronic MiniMed) were inserted into hubs placed in line with the ECLS circuit. Blood glucose was assessed with a laboratory analyzer (BG_LAB; Bayer Rapidlab 860) approximately every 5 h (mean 4.9 ± 3.3 h) with more frequent samples obtained with a bedside monitor (HemoCue) as needed. Sensor current (I_SIG) was transmitted to a laptop computer and retrospectively calibrated using BG_LAB. Sensor performance was assessed by mean absolute relative difference (MARD), linear regression slope and intercept, and correlation, all with BG_LAB as reference.

Results

The BG_LAB averaged 107.6 ± 36.4 mg/dl (mean ± standard deviation) ranging from 58 to 366 mg/dl. The MARD was 11.4%, with linear regression slope (0.86 ± 0.030) and intercept (9.0 ± 3.2 mg/dl) different from 1 and 0, respectively (p < .05), and correlation (r² = 0.76; p < .001). The system was not associated with any adverse events, and placement and removal into the hubs was easily accomplished. Instances in which more frequent BG values were obtained using a bedside HemoCue (BG_HEMO) monitor showed the sensor to respond rapidly to changes.

Conclusions

We conclude that continuous sensors can be adapted for use in an ECLS circuit with accuracy similar to or better than that achieved with the subcutaneous site. Continuous glucose monitoring in this population can rapidly detect changes in BG that would not otherwise be observed. Further studies will be needed to assess the benefit of continuous glucose monitoring in this population.