Blood glucose monitoring- an overview of current and future non-invasive devices

Background and aimsBlood glucose monitoring is very important for individuals with diabetes due to its rate determining role in medication strength adjustment and observation of possible life-threatening hypoglycemia. Possible non-invasive devices can overcome some of these burdens and could increase adherence towards checking blood glucose.MethodsData extraction methods were primarily based through various PubMed scholarly articles for real-world examples of non-invasive approaches. Additional articles were used in adjust as supplementary to the PubMed articles.ResultsNon-invasive technology is being heavily researched and could create a new market that could offer novel options for blood glucose monitoring at home. The lack of adherence for blood glucose monitoring may be tied to current blood glucose monitoring devices, which require invasive procedures that are often painful and expensive to acquire. Certain non-invasive devices have and are being developed for accurately assessing the blood glucose levels of individuals when compared to current blood glucose monitoring devices.ConclusionBlood glucose monitoring is very important for the health and safety of individuals with diabetes. It is important to consider the direct problems that may occur from the lack of adherence to blood glucose monitoring and propose options to help reduce the issues associated with current devices. Different non-invasive technologies can tailor to the needs of patients with diabetes based on the body target that is used for detection. Further research may be needed to help improve the specificity and sensitivity of certain technologies.     

Determinants of ventilatory instability and variability

This paper reviews the major mechanisms that can give rise to various forms of variability in the ventilatory pattern. First, an elevated controller gain, coupled with the presence of delays and response lags in the chemoreflex loops, can lead to instability in feedback control and give rise to periodic breathing. This form of ventilatory stability can be assessed quantitatively by employing the concept of 'loop gain'. Several different methods of estimating loop gain from steady state or dynamic respiratory measurements are discussed. An inherently stable respiratory control system can also exhibit periodic behavior due to the influence of primary fluctuations in sleep-wake state and other physiological variables, such as cardiac output and cerebral blood flow. Self-sustained, irregular ventilatory fluctuations may be generated by nonlinear dynamic interactions between various components of the respiratory control system, such as the lung vagal afferents and the respiratory pattern generator, or through the propagation of stochastic disturbances around the chemoreflex loops.     

Applications and pitfalls of hemoglobin A1C and alternative methods of glycemic monitoring

IntroductionIntensive glycemic control minimizes the risks of microvascular complications in diabetes. A1C is a convenient estimate of mean blood glucose, but is not the only marker available. The practical use and limitations of alternative markers and continuous glucose monitors are the focus of this review.MethodsPubMed and the Cochrane Library were searched for studies concerning applications or limitations of A1C, fructosamine, glycated albumin, 1,5-anhydroglucitol, skin autofluorescence, and continuous glucose monitoring. Papers reporting on strengths, limitations, or comparisons of these methods were reviewed for inclusion.ResultsA1C reflects three months of glycemic control and is not an ideal marker in all patient populations. Fructosamine and glycated albumin reflect mean blood glucose over three weeks. 1,5-Anhydroglucitol can measure hyperglycemic excursions in days to weeks. Continuous glucose monitors provide immediate feedback for timely intervention to reduce glycemic excursions and can assess glycemic variability. Current barriers to continuous glucose monitor use include inexperience, cost, discomfort, and medication interference.ConclusionsMany promising alternative glycemic markers exist. The main limitations for all alternative methods of glycemic monitoring are a lack of standardization for clinically useful cut-offs or guidelines, and a lack of long-term data on their association with complications, particularly in varied patient populations.     

Online social networking services in the management of patients with diabetes mellitus: Systematic review and meta-analysis of randomised controlled trials

AimsSocial networking services (SNS) can facilitate real-time communication and feedback of blood glucose and other physiological data between patients and healthcare professionals. This systematic review and meta-analysis aims to summarise the current evidence surrounding the role of online social networking services in diabetes care.MethodsWe performed a systematic literature review of the Medline, EMBASE and PsychINFO databases of all studies reporting HbA1c (glycated haemoglobin) as a measure of glycaemic control for social networking services in diabetes care. HbA1c, clinical outcomes and the type of technology used were extracted. Study quality and publication bias were assessed.ResultsSNS interventions beneficially reduced HbA1c when compared to controls, which was confirmed by sensitivity analysis. SNS interventions also significantly improved systolic and diastolic blood pressure, triglycerides and total cholesterol. Subgroup analysis according to diabetes type demonstrated that Type 2 diabetes patients had a significantly greater reduction in HbA1c than those with Type 1 diabetes.ConclusionsOnline SNS provide a novel, feasible approach to improving glycaemic control, particularly in patients with Type 2 diabetes. Further mechanistic and cost-effectiveness studies are required to improve our understanding of SNS and its efficacy in diabetes care.     

Glucose measurement in body fluids: A ready reckoner for clinicians

Background and aimsBlood glucose measurement is central to the diagnosis and management of patients with diabetes. Considering that a clinician relies heavily on blood (or rarely other body fluid) glucose values for decision making, an understanding of the basic aspects of glucose measurement in body fluids is necessary.MethodsA literature search was conducted in PubMed for articles in English on measurement of glucose in body fluids.ResultsGlucose can be measured in several body fluids, namely blood, interstitial fluid, urine, cerebrospinal fluid, pleural fluid and ascitic fluid in appropriate clinical settings. For blood glucose measurement, the present-day enzymatic methods have replaced the older reducing and condensation methods on account of their better accuracy. It is important to consider preanalytical factors such as sample collection, storage and transport when analyzing a laboratory blood glucose report. The measurement of glucose in interstitial fluid using continuous glucose monitoring system (CGMS) enables better understanding of glucose trends and fluctuations. The CGMS data should be reported using standard metrics which include parameters such as mean 24-h glucose, glycemic variability and time-in, below and above range. The measurement of glucose in urine sample is rarely ever used these days and should be reserved for exceptional circumstances.ConclusionThis review provides a detailed account of various aspects of glucose measurement including their evolution, pitfalls, and their utility in current clinical practice.     

The Artificial Pancreas on the Threshold of Ambulatory Use: Setting the Stage for a Critical Transition: Periodic-Zone Model Predictive Control for Diurnal Closed-Loop Operation of an Artificial Pancreas

Background

The objective of this research is an artificial pancreas (AP) that performs automatic regulation of blood glucose levels in people with type 1 diabetes mellitus. This article describes a control strategy that performs algorithmic insulin dosing for maintaining safe blood glucose levels over prolonged, overnight periods of time and furthermore was designed with outpatient, multiday deployment in mind. Of particular concern is the prevention of nocturnal hypoglycemia, because during sleep, subjects cannot monitor themselves and may not respond to alarms. An AP intended for prolonged and unsupervised outpatient deployment must strategically reduce the risk of hypoglycemia during times of sleep, without requiring user interaction.

Methods

A diurnal insulin delivery strategy based on predictive control methods is proposed. The so-called “periodic-zone model predictive control” (PZMPC) strategy employs periodically time-dependent blood glucose output target zones and furthermore enforces periodically time-dependent insulin input constraints to modulate its behavior based on the time of day.

Results

The proposed strategy was evaluated through an extensive simulation-based study and a preliminary clinical trial. Results indicate that the proposed method delivers insulin more conservatively during nighttime than during daytime while maintaining safe blood glucose levels at all times. In clinical trials, the proposed strategy delivered 77% of the amount of insulin delivered by a time-invariant control strategy; specifically, it delivered on average 1.23 U below, compared with 0.31 U above, the nominal basal rate overnight while maintaining comparable, and safe, blood glucose values.

Conclusions

The proposed PZMPC algorithm strategically prevents nocturnal hypoglycemia and is considered a significant step toward deploying APs into outpatient environments for extended periods of time in full closed-loop operation.     

Association between tear and blood glucose concentrations: Random intercept model adjusted with confounders in tear samples negative for occult blood

Aims/IntroductionTo prevent diabetic complications, strict glucose control and frequent monitoring of blood glucose levels with invasive methods are necessary. We considered the monitoring of tear glucose levels might be a possible method for non‐invasive glucose monitoring. To develop tear glucose monitoring for clinical application, we investigated the precise correlation between the blood and tear glucose concentrations.Materials and MethodsA total of 10 participants and 20 participants with diabetes were admitted, and blood and tear samples were collected. Before statistical analysis, we eliminated tear samples contaminated with blood. We observed the daily blood and tear glucose dynamics, and carried out a random intercept model analysis to examine the association between the blood and tear glucose concentrations.ResultsTear occult blood tests showed that the tear glucose concentrations and their variation increased in both participants with and without diabetes as contamination of blood increased. In both participants with and without diabetes, fluctuations of the plasma glucose concentrations were observed depending on the timing of collection of the samples, and the dynamics of the tear glucose concentrations paralleled those of the plasma glucose concentrations. The random intercept model analysis showed a significant association between the plasma and tear glucose concentrations in participants with diabetes (P < 0.001). This association still existed even after adjusting for the glycated hemoglobin levels and the prandial state (P < 0.001).ConclusionsIt is important to eliminate the tear samples contaminated with blood. Tear glucose monitoring might be a reliable and non‐invasive substitute method for monitoring the blood glucose concentrations for diabetes patients, irrespective of glycated hemoglobin levels and timing of sample collection.     

Impact of patient education on KAP,medication adherence and therapeutic outcomes of metformin versus insulin therapy in patients with gestational diabetes: A Hospital based pilot study in South India

Background and aimThe study assessed the impact of continuous patient education on Knowledge, Attitude, Practice (KAP), medication adherence and extent of glycemic control in pregnant women with gestational diabetes on insulin or metformin therapy.Methods81 women with gestational diabetes (37 on insulin and 44 on metformin) were assessed for KAP using a validated questionnaire and medication adherence using the 8-items Morisky medication adherence scale, fasting, and postprandial blood glucose levels at the baseline and after two education sessions on drug therapy at one and three months intervals. The difference in mean KAP, medication adherence scores, fasting, and postprandial blood glucose levels and the extent of glycemic control with insulin or metformin therapy were assessed statistically.ResultsThere was a highly significant difference in the mean KAP, medication adherence scores, fasting and postprandial blood glucose levels from baseline to follow-up after three months, (P < 0.0001) indicating that continuous patient education had a positive impact on their KAP, medication adherence, blood glucose levels.ConclusionThe study identified that continuous patient education improved their knowledge and practice of medication adherence which reflected on lowered fasting and postprandial blood glucose levels. Glycemic control was found to be the same with metformin and insulin in gestational diabetes.     

High Frequency of Dermatological Complications in Children and Adolescents with Type 1 Diabetes: A Web-Based Survey

Introduction:Despite advances in the management of type 1 diabetes (T1D), there is an increasing incidence of skin reactions related to diabetes devices such as patch pumps and glucose sensors. Aim of the present study was to assess the prevalence of dermatological complications in pediatric patients with T1D using technological devices.Methods:Online survey regarding skin reactions related to the use of patch pumps and/or glucose sensors was administered to families of children and adolescents (0-17 years) with T1D. Data were collected on demographic characteristics, duration of diabetes, and clinical features of dermatological complications if present.Results:Our study population consisted of 139 patients (female 51.8%) aged 11.1 ± 3.3 years. More than half (51.1%) experienced skin reactions due to patch pumps or glucose sensors. Dermatological complications were mainly caused by continuous glucose monitoring (56.3% of total). Timing of appearance of dermatological reactions varied from a few days to several months after the introduction of the device. The application of hypoallergenic barrier bandages was the most frequently adopted measure to solve the issue.Conclusions:Our study confirmed high frequency of dermatological complications among pediatric patients with type 1 diabetes. Well-designed studies are awaited to provide clear recommendations to minimize the burden of skin issues related to technological devices.     

Cyclic changes in glycemia assessed by continuous glucose monitoring system during multiple complete menstrual cycles in women with type 1 diabetes

Many women with diabetes notice changes in glucose control perimenstrually. To describe the pattern of changes in glucose control throughout the complete menstrual cycle, and the reproducibility of these changes, we performed a pilot study evaluating glycemic profiles continuously for three cycles in four women with type 1 diabetes. All participants had hemoglobin A1c <7.5% and regular menstrual periods off oral contraceptives. They used Medtronic MiniMed (Northridge, CA) Continuous Glucose Monitoring System (CGMS) devices continuously for three complete menstrual cycles, checked capillary glucose measurements six times daily, changed their own sensors every 3 days, and were seen seven times per menstrual cycle to download data and draw blood. Prolonged monitoring was safely carried out over three consecutive menstrual cycles. We observed two different patterns of glycemic control in relation to the menstrual cycle in these women. The first pattern, seen in two women, was characterized by increased frequency of hyperglycemia in the luteal phase. One of these women also had a hyperglycemic peak in the follicular phase. In the other two women, no characteristic cycle-related pattern was noted. The glucose profiles appeared reproducible between cycles in all women, but varied between women. Thus the menstrual cycle has a reproducible effect on glucose control in a subset of women with type 1 diabetes. Prolonged use of continuous glucose monitoring was safe in the subjects studied, and is the first method clinically available to monitor glucose control over prolonged periods in individuals with diabetes.     

Influence of glucose,insulin fluctuation,and glycosylated hemoglobin on the outcome of sarcopenia in patients with type 2 diabetes mellitus

AimsTo explore the effects of glucose, insulin, and glycosylated hemoglobin (HbA1c) levels on the outcome of sarcopenia in patients with type 2 diabetes mellitus (T2DM).MethodsA total of 482 T2DM patients were enrolled in the follow-up study. The median follow-up time was 36 months. Muscle mass and HbA1c were measured in all participants. And glucose, C-peptide and insulin levels were measured at 0 min, 30 min, and 120 min after glucose load. We subsequently analyzed daily glucose fluctuations and islet function before and after readmission as well as the influence of their changes on sarcopenia outcome.ResultsAfter glucose load, incident sarcopenia patients showed greater glucose fluctuations and worse islet function than did non-sarcopenia patients. As HbA1c and standard deviation of blood glucose (SDBG) increased, readmitted non-sarcopenia patients showed a significantly increased odds ratio of incident sarcopenia; however, only patients with higher quartiles were statistically significant. Increased ΔAUC-C-peptide reduced the risk of incident sarcopenia (P < 0.05).ConclusionsPatients with incident sarcopenia have poor glucose regulation and insufficient insulin secretion. Furthermore, as HbA1c and SDBG increased, AUC-C-peptide and AUC-insulin decreased in readmitted non-sarcopenia patients, the risk of incident sarcopenia increased.     

Exercise and the Development of the Artificial Pancreas: One of the More Difficult Series of Hurdles

Regular physical activity (PA) promotes numerous health benefits for people living with type 1 diabetes (T1D). However, PA also complicates blood glucose control. Factors affecting blood glucose fluctuations during PA include activity type, intensity and duration as well as the amount of insulin and food in the body at the time of the activity. To maintain equilibrium with blood glucose concentrations during PA, the rate of glucose appearance (Ra) to disappearance (Rd) in the bloodstream must be balanced. In nondiabetics, there is a rise in glucagon and a reduction in insulin release at the onset of mild to moderate aerobic PA. During intense aerobic -anaerobic work, insulin release first decreases and then rises rapidly in early recovery to offset a more dramatic increase in counterregulatory hormones and metabolites. An “exercise smart” artificial pancreas (AP) must be capable of sensing glucose and perhaps other physiological responses to various types and intensities of PA. The emergence of this new technology may benefit active persons with T1D who are prone to hypo and hyperglycemia.     

Effects of sleep intervention on glucose control: A narrative review of clinical evidence

BackgroundOptimizing sleep has been recently gained exposure as a promising lifestyle consideration to aid in the control of diabetes. The evidence to support the impact of sleep quantity and quality on blood glucose control is largely acknowledged. This study aimed to review all published randomized controlled trials (RCTs) investigating the relationship between sleep and glucose control to synthesize an accurate overview.MethodLiterature from PubMed and Google Scholar was searched using the listed search terms to obtain RCTs on the role of sleep in glucose homeostasis. Seven RCTs were eligible and included in our review. References in these RCTs were screened for the presentation of the pathophysiology of metabolic disturbances relating to the sleep duration, and the relevant factors affecting blood glucose concentration.ResultsSleep deprivation and poor sleep quality are connected with blood glucose disturbance and reduction of insulin sensitivity. This leaves diabetic patients at an increased risk of glucose level fluctuations. However, the function of β-cells was likely to be conserved after 14-days of sleep deprivation. Sleep extension from 7 to 14 days improved blood glucose control and insulin sensitivity in both healthy and diabetes participants. Diabetes sleep education and personalized interventions that reduced stress and improved sleep quality contributed to glucose homeostasis in diabetic patients. Overall improving one’s sleep hygiene was found to improve glucose control in diabetic patients.ConclusionLonger or short-term sleep deprivation may negatively affect glucose homeostasis, although the body temporarily compensates for the impaired function of β-cells when reduced sleep lasted up to 14 days. Thus, we recommend optimum sleep duration and optimistic sleep duration and sleep quality for decreasing risk and progression of diabetes.     

Evolution of devices in diabetes management

Recent technological advancements in insulin administration and glucose monitoring have allowed patients with diabetes to become increasingly involved in their own care. Devices replacing the traditional vial and syringe, such as insulin pens, are gaining popularity and offer simple and convenient insulin administration. Pen devices are associated with improved dose accuracy, reducing the risk of hypo- or hyperglycemia, and are continually being updated with new safety features in order to optimize their performance. In patients for whom glucose variability remains a problem, continuous subcutaneous insulin infusion via an implanted canula or continuous intraperitoneal insulin infusion via an implanted pump is safe and effective when used correctly, although cost can be a limitation. More accurate retrospective and real-time continuous monitoring devices, which can better detect blood glucose excursions, have become standard components of modern-day diabetes management. The most recent devices have sensor-signaling capabilities with wireless data transmission, leading to reduced time delay and more accurate alerts. Ultimately, though, while self-management remains a critical factor in improving glycemic control at present, human error may undermine even the most accurate treatment interventions. A key long-term goal in diabetes management is, therefore, to develop an automated and accurate closed-loop system for blood glucose monitoring and insulin delivery to better reflect the physiological mechanisms of glucose homeostasis and remove the "human" element. This "artificial pancreas" would offer the most innovative intervention for diabetes management and has the potential to considerably reduce the patient's burden of self-care.     

Modeling Ketogenesis for Use in Pediatric Diabetes Simulation

Background:Simulation is being increasingly integrated into medical education. Diabetes simulation is well-received by trainees and has demonstrated improved clinical results, including reduced adult inpatient hyperglycemia. However, no pediatric-specific diabetes simulation programs exist for use in medical education. None of the existing diabetes models incorporate ketones as an input or an output, which is essential for use in teaching pediatric diabetes management.Methods:We created a pediatric diabetes simulation incorporating both blood sugar and urine ketones as output. Ketone output is implemented as a state variable but is obfuscated to simulate hospital experience. Blood sugar output is similar to other models and incorporates the current blood sugar, insulin on board (IOB) and carbohydrates on board (COB), and insulin and carbohydrate sensitivities. The program calculates all IOB and COB every 15 minutes based on user input and provides written summary feedback at the end of the simulation about inaccurate dosing and timing.Results:The simulation realistically incorporated both blood glucose and urine ketones in clinically valid and actionable formats. After completing this simulation, 16/17 pediatric residents indicated that they wanted more simulated diabetes cases integrated into their curriculum.Conclusion:Implementing simulation into pediatric diabetes education was feasible and well-received. More work is needed to further study the role of simulation in pediatric diabetes education when used adjunctively or in lieu of lectures when time or resources are limited.     

Assessment of the “Second Day” Exercise Effect on Glycemic Control,Insulin Requirements,and CHO Intake in Type 1 Diabetes Adults

Background:Glucose control during consecutive days of aerobic exercise has not been well studied. We assessed glycemia, insulin requirements, and carbohydrate (CHO) needs during two consecutive days of prolonged cycling in type 1 diabetes (T1D) adults using sensor-augmented insulin pump therapy.Methods:Twenty adults with well-controlled T1D and six healthy adults (for comparison) were enrolled. Assessments were made during two consecutive days of cycling activities (30 miles per day). On day 1 (D1), basal rates were reduced 50% and CHO intake was guided by real-time continuous glucose monitoring (rtCGM) data to maintain a target range (70-180 mg/dL). On day 2 (D2), basal insulin infusion was stopped for the first hour of biking and resumed at a minimal rate during biking. Carbohydrate intake one hour before, during, and ten minutes after biking was recorded. Times within/below target range, glycemic variability, and mean glucose were calculated from rtCGM data.Results:Among 17 T1D participants who completed the study, mean glucose levels at the start of cycling were slightly lower on D2 vs D1: 138 ± 16 mg/dL and 122 ± 16, respectively, P = NS. Type 1 diabetes participants achieved near-normal glucose levels at the end of both cycling events; however, the reduction in glucose was most notable at one hour into the event on D2 vs D1. Carbohydrate intake was notably lower during D2 vs D1 with no difference in time <54 mg/dL (both P = NS).Conclusions:Type 1 diabetes individuals using rtCGM-augmented insulin pump therapy can safely engage in consecutive days of prolonged aerobic exercise by significantly reducing insulin dosages with no increase in CHO intake.     

Delays in Minimally Invasive Continuous Glucose Monitoring Devices: A Review of Current Technology

Through the use of enzymatic sensors—inserted subcutaneously in the abdomen or ex vivo by means of microdialysis fluid extraction—real-time minimally invasive continuous glucose monitoring (CGM) devices estimate blood glucose by measuring a patient''s interstitial fluid (ISF) glucose concentration. Signals ac-quired from the interstitial space are subsequently calibrated with capillary blood glucose samples, a method that has raised certain questions regarding the effects of physiological time lags and of the duration of processing delays built into these devices. The time delay between a blood glucose reading and the value displayed by a continuous glucose monitor consists of the sum of the time lag between ISF and plasma glucose, in addition to the inherent electro-chemical sensor delay due to the reaction process and any front-end signal-processing delays required to produce smooth traces. Presented is a review of commercially available, minimally invasive continuous glucose monitors with manufacturer-reported device delays. The data acquisition process for the Medtronic MiniMed (Northridge, CA) continuous glucose monitoring system—CGMS® Gold—and the Guardian® RT monitor is described with associated delays incurred for each processing step. Filter responses for each algorithm are examined using in vitro hypoglycemic and hyperglycemic clamps, as well as with an analysis of fast glucose excursions from a typical meal response. Results demonstrate that the digital filters used by each algorithm do not cause adverse effects to fast physiol-ogic glucose excursions, although nonphysiologic signal characteristics can produce greater delays.     

Evaluation of the Utility of a Glycemic Pattern Identification System

Background:With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes.Method:To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows.Results:Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification.Conclusions:The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control.     

Continuous glucose monitoring: reliable measurements for up to 4 days with the SCGM1 system

Continuous glucose monitoring allows patients with diabetes to check their metabolic status throughout the day, including rarely monitored time periods, such as postprandial and nocturnal periods. The performance of a prototype of the novel SCGM1 System (Roche Diagnostics GmbH, Mannheim, Germany) employing the microdialysis technique was evaluated. Forty-two patients with type 1 diabetes participated in the study [29 males/13 females, age 34 +/- 9 years, duration of diabetes 16 +/- 11 years, glycated hemoglobin 7.7 +/- 1.2% (mean +/- SD)]. Forty-seven experiments were performed at four different investigational sites. A microdialysis catheter was inserted into the subcutaneous tissue of the patient's abdominal wall. Glucose was extracted from the interstitial fluid, and glucose levels were determined and stored by the SCGM1 System continuously for the duration of the experiment. Capillary blood glucose was measured frequently (at least 10 times per day) and used for linear retrospective calibration. The patients were instructed to maintain their normal diet and insulin therapy. Thirty experiments (mean duration 103 +/- 18 h) were analyzed in detail. The mean deviation of the calibrated glucose sensor values from the capillary blood glucose values (expressed as percent predicted error sum of squares) was <12.5% in 25 and <20% for all of the 30 experiments analyzed. The percent median absolute difference between the calibrated values and the reference values was <10% in 28 experiments, with a median of 5.8% for all 30 experiments. The error grid analysis of all 30 experiments showed that 99.5% of all 1,195 pairs' values were in zones A and B with only 0.2% in zone C and 0.3% in zone D. Thus the microdialysis technique employed by the SCGM1 System allows precise and accurate continuous glucose monitoring over prolonged periods of time. It appears also that effective monitoring of acute metabolic deteriorations is possible.