Glucose metabolism

The markedly increased peri-interventional risk (PCI and CABG) in patients with type-2 diabetes mellitus may be reduced by adjusting blood glucose values to a near-normal level. This adjustment should be realized acutely by glucose-insulin-potassium infusions. In long-term therapy, the target value should be achieved independent of the pharmacological principle of blood glucose reduction. Among the available oral antidiabetic agents, metformin, acarbose and glitazones seem to be cardioprotective via pleotropic effects. Given an optimal stent implantation and administration of GP IIb/IIIa inhibitors during coronary interventions, results are similar to those of non-diabetics.     

Passive Diffusion of Transdermal Glucose: Noninvasive Glucose Sensing Using a Fluorescent Glucose Binding Protein

The motivation for this study was to determine if a statistically significant correlation exists between blood glucose (BG) and transdermal glucose (TG) collected by passive diffusion. A positive outcome will indicate that noninvasive passive TG diffusion is a painless alternative to collecting blood through a break on the skin. Sampling involves placing a small volume of buffer solution on the surface of membrane or skin for 5 minutes. The sample is then assayed with fluorescent GBP. In vitro testing was done on regenerated cellulose and a porcine skin model to determine diffusion of standard glucose solutions. In vivo testing was done on a healthy subject and a subject with type 2 diabetes. Glucose diffused readily through the regenerated cellulose membrane with good correlation between surface and internal glucose concentrations (R ² = .997). But the porcine skin model required a surface prewash to achieve the same good correlation R ² = .943). Based on this, an optimum prewash step was determined for the in vivo studies. The resulting correlation coefficients between TG and BG after a 15-minute prewash in a healthy subject and type 2 subject were .87 and .93, respectively. Removal of the extraneous glucose in the skin by prewashing was an important step in achieving good correlation between TG and BG. The results suggest that passive collection of TG is a noninvasive alternative to current practice of breaking the skin. Further studies are under way to determine the lag time between TG and BG and for the sampling protocol to be more amenable to point-of-care application.     

Fluorescence Glucose Sensing,Part II: Blood Glucose Self-Monitoring with a Long-Term Subconjunctival Glucose Sensor

Background

To evaluate the feasibility of an implantable subconjunctival glucose monitoring system (SGMS) for long-term glucose monitoring, we investigated the in vivo performance of the system.

Method

The SGMS consists of an implantable ocular mini implant (OMI) and a handheld fluorescence photometer. A clinical study was performed on 47 diabetes patients split into two cohorts. Two different types of OMI were used, with and without a biocompatible surface coating. Duration of the study was 1 year. Correlation between capillary blood glucose and SGMS-derived interstitial fluid glucose was investigated during the first 6 months of the study.

Results

Both OMI types were tolerated well in the eyes of the patients. At the beginning of the study, the SGMS of both cohorts revealed a high accuracy with mean absolute relative difference (MARD) values of 7–12%. The performance of the uncoated OMIs deteriorated within 3 months of wearing time, exhibiting a MARD value of 20%. The performance of the surface-coated OMIs was preserved longer. Glucose correlation measurement with reasonable results (MARD of 14%) could be performed for up to 6 months of wear.

Conclusions

The biocompatible surface coating on the OMIs enabled a longer duration of action of up to 6 months compared with 3 months for uncoated implants in a clinical trial.     

Random Plasma Glucose in Serendipitous Screening for Glucose Intolerance: Screening for Impaired Glucose Tolerance Study 2

Background With positive results from diabetes prevention studies, there is interest in convenient ways to incorporate screening for glucose intolerance into routine care and to limit the need for fasting diagnostic tests. Objective The aim of this study is to determine whether random plasma glucose (RPG) could be used to screen for glucose intolerance. Design This is a cross-sectional study. Participants The participants of this study include a voluntary sample of 990 adults not known to have diabetes. Measurements RPG was measured, and each subject had a 75-g oral glucose tolerance test several weeks later. Glucose intolerance targets included diabetes, impaired glucose tolerance (IGT), and impaired fasting glucose₁₁₀ (IFG₁₁₀; fasting glucose, 110–125 mg/dl, and 2 h glucose < 140 mg/dl). Screening performance was measured by area under receiver operating characteristic curves (AROC). Results Mean age was 48 years, and body mass index (BMI) was 30.4 kg/m²; 66% were women, and 52% were black; 5.1% had previously unrecognized diabetes, and 24.0% had any “high-risk” glucose intolerance (diabetes or IGT or IFG₁₁₀). The AROC was 0.80 (95% CI 0.74–0.86) for RPG to identify diabetes and 0.72 (0.68–0.75) to identify any glucose intolerance, both highly significant (p < 0.001). Screening performance was generally consistent at different times of the day, regardless of meal status, and across a range of risk factors such as age, BMI, high density lipoprotein cholesterol, triglycerides, and blood pressure. Conclusions RPG values should be considered by health care providers to be an opportunistic initial screening test and used to prompt further evaluation of patients at risk of glucose intolerance. Such “serendipitous screening” could help to identify unrecognized diabetes and prediabetes.     

Predicting Plasma Glucose From Interstitial Glucose Observations Using Bayesian Methods

One way of constructing a control algorithm for an artificial pancreas is to identify a model capable of predicting plasma glucose (PG) from interstitial glucose (IG) observations. Stochastic differential equations (SDEs) make it possible to account both for the unknown influence of the continuous glucose monitor (CGM) and for unknown physiological influences. Combined with prior knowledge about the measurement devices, this approach can be used to obtain a robust predictive model. A stochastic-differential-equation-based gray box (SDE-GB) model is formulated on the basis of an identifiable physiological model of the glucoregulatory system for type 1 diabetes mellitus (T1DM) patients. A Bayesian method is used to estimate robust parameters from clinical data. The models are then used to predict PG from IG observations from 2 separate study occasions on the same patient. First, all statistically significant diffusion terms of the model are identified using likelihood ratio tests, yielding inclusion of σ_Isc, σ_Gp, and σ_Gsc. Second, estimates using maximum likelihood are obtained, but prediction capability is poor. Finally a Bayesian method is implemented. Using this method the identified models are able to predict PG using only IG observations. These predictions are assessed visually. We are also able to validate these estimates on a separate data set from the same patient. This study shows that SDE-GBs and a Bayesian method can be used to identify a reliable model for prediction of PG using IG observations obtained with a CGM. The model could eventually be used in an artificial pancreas.     

Impaired Glucose Tolerance

Impaired glucose tolerance (IGT) is determined by measuring plasma glucose levels 2 hours after glucose loading in the oral glucose tolerance test. There is good evidence from epidemiologic and prospective trials [e.g. Diabetes Epidemiology: Collaborative Analysis of Diagnostic Criteria in Europe (DECODE)] linking IGT with the development of type 2 diabetes mellitus and cardiovascular disease (CVD). IGT is characterized by an increase in postprandial glucose levels, which is considered the earliest metabolic abnormality in type 2 diabetes mellitus. It is one of a series of risk factors for CVD (hypertension, high triglyceride levels, low high-density lipoprotein-cholesterol and central obesity), known as the metabolic syndrome. The different factors making up this syndrome are intimately related. An impaired lipid profile can contribute to insulin resistance, as IGT may play a pathogenic role on other cardiovascular risk factors. IGT is the first easily identifiable step in the pathophysiology of type 2 diabetes mellitus. It is associated with high risk for type 2 diabetes mellitus and subsequent vascular morbidity and mortality. It is currently unknown whether treating IGT will reduce the incidence of macrovascular complications, as studies addressing this issue have yet to be conducted. Therefore, the main reason to identify and treat IGT is to prevent or delay the onset of type 2 diabetes mellitus. It has been demonstrated that lifestyle intervention with diet and exercise can reduce the incidence of type 2 diabetes mellitus. Pharmacologic intervention with metformin and acarbose is also effective. Other drugs, such as those indicated to treat other parameters of the metabolic syndrome, may also be useful. We can now be assured that prevention or delay of onset of type 2 diabetes mellitus is possible in individuals with IGT, either by changes in lifestyle or by pharmacotherapy.     

Fluorescence Glucose Sensing,Part II: Fluorescence Intensity- and Lifetime-Based Glucose Sensing Using Glucose/Galactose-Binding Protein

We review progress in our laboratories toward developing in vivo glucose sensors for diabetes that are based on fluorescence labeling of glucose/galactose-binding protein. Measurement strategies have included both monitoring glucose-induced changes in fluorescence resonance energy transfer and labeling with the environmentally sensitive fluorophore, badan. Measuring fluorescence lifetime rather than intensity has particular potential advantages for in vivo sensing. A prototype fiber-optic-based glucose sensor using this technology is being tested.Fluorescence technique is one of the major solutions for achieving the continuous and noninvasive glucose sensor for diabetes. In this article, a highly sensitive nanostructured sensor is developed to detect extremely small amounts of aqueous glucose by applying fluorescence energy transfer (FRET). A one-pot method is applied to produce the dextran-fluorescein isothiocyanate (FITC)-conjugating mesoporous silica nanoparticles (MSNs), which afterward interact with the tetramethylrhodamine isothiocyanate (TRITC)-labeled concanavalin A (Con A) to form the FRET nanoparticles (FITC-dextran-Con A-TRITC@MSNs). The nanostructured glucose sensor is then formed via the self-assembly of the FRET nanoparticles on a transparent, flexible, and biocompatible substrate, e.g., poly(dimethylsiloxane). Our results indicate the diameter of the MSNs is 60 ± 5 nm. The difference in the images before and after adding 20 μl of glucose (0.10 mmol/liter) on the FRET sensor can be detected in less than 2 min by the laser confocal laser scanning microscope. The correlation between the ratio of fluorescence intensity, I(donor)/I(acceptor), of the FRET sensor and the concentration of aqueous glucose in the range of 0.04–4 mmol/liter has been investigated; a linear relationship is found. Furthermore, the durability of the nanostructured FRET sensor is evaluated for 5 days. In addition, the recorded images can be converted to digital images by obtaining the pixels from the resulting matrix using Matlab image processing functions. We have also studied the in vitro cytotoxicity of the device. The nanostructured FRET sensor may provide an alternative method to help patients manage the disease continuously.     

An Analysis of How to Measure Glucose during Glucose Clamps: Are Glucose Meters Ready for Research?

This article provides a perspective on the challenges of appropriate glucose measurement in the context of glucose clamp experiments. In a first step, the core outcome parameters of a clamp experiment, the blood glucose target level, and the glucose infusion rate will be identified. The relation of these core parameters to glucose measurement are discussed. From there, the core quality parameters of glucose measurement within a clinical research setting are identified and assessed in light of their practical implications, with a specific consideration of the work presented by Cohen et al. in this issue of the Journal of Diabetes Science and Technology.     

Basement Membrane-Based Glucose Sensor Coatings Enhance Continuous Glucose Monitoring in Vivo

Background:

Implantable glucose sensors demonstrate a rapid decline in function that is likely due to biofouling of the sensor. Previous efforts directed at overcoming this issue has generally focused on the use of synthetic polymer coatings, with little apparent effect in vivo, clearly a novel approach is required. We believe that the key to extending sensor life span in vivo is the development of biocompatible basement membrane (BM) based bio-hydrogels as coatings for glucose sensors.

Method:

BM based bio-hydrogel sensor coatings were developed using purified BM preparations (ie, Cultrex from Trevigen Inc). Modified Abbott sensors were coated with Cultrex BM extracts. Sensor performance was evaluated for the impact of these coatings in vitro and in vivo in a continuous glucose monitoring (CGM) mouse model. In vivo sensor function was assessed over a 28-day time period expressed as mean absolute relative difference (MARD) values. Tissue reactivity of both Cultrex coated and uncoated glucose sensors was evaluated at 7, 14, 21 and 28 days post–sensor implantation with standard histological techniques.

Results:

The data demonstrate that Cultrex-based sensor coatings had no effect on glucose sensor function in vitro. In vivo glucose sensor performance was enhanced following BM coating as determined by MARD analysis, particularly in weeks 2 and 3. In vivo studies also demonstrated that Cultrex coatings significantly decreased sensor-induced tissue reactions at the sensor implantation sites.

Conclusion:

Basement-membrane-based sensor coatings enhance glucose sensor function in vivo, by minimizing or preventing sensor-induced tissues reactions.     

糖尿病患者的血糖及尿糖检验临床分析

目的探究糖尿病患者血糖及尿糖检验的临床价值。方法选取2018年1月—2019年12月林甸县鹤鸣湖镇卫生院收治的60例糖尿病患者作为研究对象,电脑随机数字表法分组,每组30例。对照组给予尿糖检验,观察组采用血糖检验。比较两种诊断方式准确率及血浆葡萄糖水平。结果观察组与对照组对糖尿病诊断准确率分别为93.3%、70.0%,组间差异有统计学意义(P<0.05)。结论血糖检验应用于糖尿病患者,诊断准确率高,且能够有效检出不同时段血浆葡萄糖水平,优于尿糖检验,可予以推广。     

Optimum Subcutaneous Glucose Sampling and Fourier Analysis of Continuous Glucose Monitors

Background

The objective of this article was to focus on the application of harmonic decomposition to continuous glucose monitor (CGM) measurements. We show evidence of an attenuation of fast variations of interstitial glucose when compared to blood in type 1 diabetes mellitus (T1DM) and, using information theory, propose optimal sampling schedules associated with the use and study of CGMs.

Method

Using a cohort of 26 T1DM subjects, wearing two Navigator™ sensors for 1 to 3 days, we analyzed the frequency content of each glucose signal and derived across subject frequency cutoffs using discrete Fourier transform and common signal processing techniques.

Results

We observed a significant difference in the frequency content of blood glucose compared to interstitial glucose in T1DM, providing evidence toward the existence of a diffusion process between blood and interstitial glucose, acting as a low-pass filter. Furthermore, we obtained a 15-minutes sampling schedule for optimal comparison of CGM values to blood reference.

Conclusion

Blood glucose and interstitial glucose have different dynamics, as shown by harmonic analysis, and these differences have consequences on advisable schedules for accuracy studies of CGMS.     

Alarms for Continuous Glucose Monitors: Alarm Characterization for a Continuous Glucose Monitor That Replaces Traditional Blood Glucose Monitoring

Background

Continuous glucose monitoring (CGM) devices available in the United States are approved for use as adjuncts to self-monitoring of blood glucose (SMBG); all CGM alarms require SMBG confirmation before treatment. In this report, an analysis method is proposed to determine the CGM threshold alarm accuracy required to eliminate SMBG confirmation.

Method

The proposed method builds on the Clinical and Laboratory Standards Institute (CLSI) guideline for evaluating CGM threshold alarms using data from an in-clinic study of subjects with type 1 diabetes. The CLSI method proposes a maximum time limit of ±30 minutes for the detection of hypo- and hyperglycemic events but does not include limits for glucose measurement accuracy. The International Standards Organization (ISO) standard for SMBG glucose measurement accuracy (ISO 15197) is ±15 mg/dl for glucose <75 mg/dl and ±20% for glucose ≥75 mg/dl. This standard was combined with the CLSI method to more completely characterize the accuracy of CGM alarms.

Results

Incorporating the ISO 15197 accuracy margins, FreeStyle Navigator® CGM system alarms detected 70 mg/dl hypoglycemia within 30 minutes at a rate of 70.3%, with a false alarm rate of 11.4%. The device detected high glucose in the range of 140–300 mg/dl within 30 minutes at an average rate of 99.2%, with a false alarm rate of 2.1%.

Conclusion

Self-monitoring of blood glucose confirmation is necessary for detecting and treating hypoglycemia with the FreeStyle Navigator CGM system, but at high glucose levels, SMBG confirmation adds little incremental value to CGM alarms.     

No-Coding Strategies for Glucose Monitors: Predicted Blood Glucose from Insulin Administration Based on Values from Miscoded Glucose Meters

Objectives

The proper use of many types of self-monitored blood glucose (SMBG) meters requires calibration to match strip code. Studies have demonstrated the occurrence and impact on insulin dose of coding errors with SMBG meters. This paper reflects additional analyses performed with data from Raine et al. (JDST, 2:205–210, 2007). It attempts to relate potential insulin dose errors to possible adverse blood glucose outcomes when glucose meters are miscoded.

Methods

Five sets of glucose meters were used. Two sets of meters were autocoded and therefore could not be miscoded, and three sets required manual coding. Two of each set of manually coded meters were deliberately miscoded, and one from each set was properly coded. Subjects (n = 116) had finger stick blood glucose obtained at fasting, as well as at 1 and 2 hours after a fixed meal (Boost^®; Novartis Medical Nutrition U.S., Basel, Switzerland). Deviations of meter blood glucose results from the reference method (YSI) were used to predict insulin dose errors and resultant blood glucose outcomes based on these deviations.

Results

Using insulin sensitivity data, it was determined that, given an actual blood glucose of 150–400 mg/dl, an error greater than +40 mg/dl would be required to calculate an insulin dose sufficient to produce a blood glucose of less than 70 mg/dl. Conversely, an error less than or equal to -70 mg/dl would be required to derive an insulin dose insufficient to correct an elevated blood glucose to less than 180 mg/dl.For miscoded meters, the estimated probability to produce a blood glucose reduction to less than or equal to 70 mg/dl was 10.40%. The corresponding probabilities for autocoded and correctly coded manual meters were 2.52% (p < 0.0001) and 1.46% (p < 0.0001), respectively.Furthermore, the errors from miscoded meters were large enough to produce a calculated blood glucose outcome less than or equal to 50 mg/dl in 42 of 833 instances. Autocoded meters produced zero (0) outcomes less than or equal to 50 mg/dl out of 279 instances, and correctly coded manual meters produced 1 of 416.

Conclusions

Improperly coded blood glucose meters present the potential for insulin dose errors and resultant clinically significant hypoglycemia or hyperglycemia. Patients should be instructed and periodically reinstructed in the proper use of blood glucose meters, particularly for meters that require coding.     

The Impact of Continuous Glucose Monitoring on Low Interstitial Glucose Values and Low Blood Glucose Values Assessed by Point-of-care Blood Glucose Meters: Results of a Crossover Trial

In a randomized crossover trial the impact of continuous glucose monitoring (CGM) was tested on the occurrence of low blood glucose values measured by point of care (POC) measurement and on low glucose values measured by CGM in the interstitial fluid. A total of 41 type 1 diabetic patients (age 42.0 ± 11.4 years, diabetes duration 15.3 ± 10.1 years, A1c 8.2 ± 1.4%) used a CGM system (Dexcom SEVEN PLUS system) twice. In first study phase (CGM blind), patients were blind regarding the CGM current glucose levels and were not alerted when critical glucose values were reached. In the second phase (CGM real time), patients had access to current glucose levels and were alerted if critical glucose values were reached. During CGM real time the proportion of hypoglycemic POC blood glucose values were significantly reduced (7.5 ± 5.6% vs 10.1 ± 7.5%; P = .04), whereas the proportion of euglycemic blood glucose values were significantly enhanced (73.7 ± 18.3% vs 68.3 ± 12.1%; P = .01). The duration of low glucose periods in the interstitial fluid was significantly lower in the CGM real time phase (125 ± 89 vs 181 ± 125 minutes per day; P = .005). The time until a low blood glucose was detected by POC measurement was shortened by 33.2 ± 76.1 minutes (P = .03). The study demonstrated that CGM is able to not only reduce duration of hypoglycemia measured by CGM in interstitial fluid, but also reduce the proportion of low POC blood glucose measurements. In addition, hypoglycemia can be detected earlier.     

Fluorescence Glucose Sensing,Part II: Single-Walled Carbon Nanotube-Based Near-Infrared Optical Glucose Sensors toward In Vivo Continuous Glucose Monitoring

This article reviews research efforts on developing single-walled carbon nanotube (SWNT)-based near-infrared (NIR) optical glucose sensors toward long-term in vivo continuous glucose monitoring (CGM). We first discuss the unique optical properties of SWNTs and compare SWNTs with traditional organic and nanoparticle fluorophores regarding in vivo glucose-sensing applications. We then present our development of SWNT-based glucose sensors that use glucose-binding proteins and boronic acids as a high-affinity molecular receptor for glucose and transduce binding events on the receptors to modulate SWNT fluorescence. Finally, we discuss opportunities and challenges in translating the emerging technology of SWNT-based NIR optical glucose sensors into in vivo CGM for practical clinical use.     

Parameters Affecting Postprandial Blood Glucose: Effects of Blood Glucose Measurement Errors

Background

The Diabetes Error Test Model (DETM) has been developed to characterize the clinical relevance of the large and varying margins of error of parameters affecting postprandial blood glucose (BG) levels, which increase the risk for hypo- or hyperglycemia.

Methods

The DETM is based on a treatment concept aimed at normoglycemia after meals. The model includes as parameters (a) preprandial BG measurement by patient self-monitoring (SMBG), (b) patient estimate of carbohydrate amounts (CARB-P) in food, (c) effect of CARB-P on maximum BG increase, (d) effect of insulin on maximum BG decrease, and (e) insulin dosage. Covering the relevant range of preprandial BG (30–330 mg/dl), the DETM simulates the maximum effect of these parameters and their margins of error on postprandial BG values.

Results

According to the DETM, a SMBG error of +20% results in normoglycemia (BG range: 60–160 mg/dl) as the postprandial outcome if preprandial BG values are in the range of 30–130 or 260–330 mg/dl, but can unexpectedly result in hypoglycemia if preprandial BG values are between 131 and 259 mg/dl. If the SMBG error of +20% is combined, e.g., with an error of CARB-P estimate in the food of +20%, hypoglycemia as the postprandial outcome is worsened. If one combines the effects of errors of more than two parameters, even with errors that are so small that they have no clinically relevant dysglycemic effect on postprandial BG per se (e.g., ±6%), this can result in postprandial hypo- or hyperglycemic values.

Conclusion

The DETM simulates the effects of errors of parameters affecting postprandial BG within the clinically relevant BG range. The DETM offers the opportunity to evaluate the clinical relevance of these errors and their contribution to the increased risk of meal-related excessive glucose excursions during intensified insulin therapy.     

Agreement between Glucose Trends Derived from Three Simultaneously Worn Continuous Glucose Sensors

Background

Sensors detect the rate and direction of glucose trend. They need to be accurate and reproducible as could be evidenced by strong agreement between multiple sensors. We evaluated this relationship through simultaneously worn glucose sensors using several methods of slope analysis.

Methods

Ten type 1 diabetic, insulin pump-treated subjects were studied while simultaneously wearing three CGMS^® Gold sensors each. Sensors were placed in the right abdomen (reference), left abdomen, and left upper arm. Sensors were calibrated and chronologically aligned. Data were only interpreted and included if there were 24 hours of data simultaneously obtained from all three sensors.

Results

Using a two-point derived slope, increasing the duration of the trend from 5 to 60 minutes improved agreement between sensors. Using a 20-minute rolling average trend (using every 5-minute glucose value during the 20 minutes) improved the agreement to 94.3%. Finally, using whichever of the two comparator sensor rolling average trends was closest to the reference (better of two), the agreement improved to 98.2%. However, for these trend analysis methods, when the absolute reference rate of change was more than 1 mg/dl/min, the agreement decreased. Even with the best analysis approach, at an absolute reference sensor rate of change of >2 mg/dl/min, the agreement between sensors was only 40.0%.

Conclusion

Despite several methods of analysis, trend agreement from multiple sensors diminishes as the absolute rate of change of reference glucose increases.     

Alarms for Continuous Glucose Monitors: Alarm Characterization for Continuous Glucose Monitors Used as Adjuncts to Self-Monitoring of Blood Glucose

Background

Continuous glucose monitoring (CGM) devices available in the United States are approved for use as adjuncts to self-monitoring of blood glucose (SMBG). Alarm evaluation in the Clinical and Laboratory Standards Institute (CLSI) guideline for CGM does not specifically address devices that employ both CGM and SMBG. In this report, an alarm evaluation method is proposed for these devices.

Method

The proposed method builds on the CLSI method using data from an in-clinic study of subjects with type 1 diabetes. CGM was used to detect glycemic events, and SMBG was used to determine treatment. To optimize detection of a single glucose level, such as 70 mg/dl, a range of alarm threshold settings was evaluated. The alarm characterization provides a choice of alarm settings that trade off detection and false alarms. Detection of a range of high glucose levels was similarly evaluated.

Results

Using low glucose alarms, detection of 70 mg/dl within 30 minutes increased from 64 to 97% as alarm settings increased from 70 to100 mg/dl, and alarms that did not require treatment (SMBG >85 mg/dl) increased from 18 to 52%. Using high glucose alarms, detection of 180 mg/dl within 30 minutes increased from 87 to 96% as alarm settings decreased from 180 to 165 mg/dl, and alarms that did not require treatment (SMBG <180 mg/dl) increased from 24 to 42%.

Conclusion

The proposed alarm evaluation method provides information for choosing appropriate alarm thresholds and reflects the clinical utility of CGM alarms.