Capillary Glucose Readings Research Articles

Noninvasive Real-Time Glucose Monitoring Is in the Near Future.

Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n = 6; type 1 diabetes, n = 28; nondiabetic pregnant subjects, n = 10; and nondiabetic, n = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors (R2 = 0.95), with 100% of values within Zone A. In the hypoglycemia assessment, measurements from the Gen III sensor tightly followed the capillary glucose measurements down to 42 mg/dL (2.3 mmol/L), whereas the CGM measurements from two different CGM only converged with the GWave and capillary glucose readings after 90 min of decreasing glucose levels. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.

Remission of Type 2 Diabetes Following a Short-term Intensive Intervention With Insulin Glargine, Sitagliptin, and Metformin: Results of an Open-label Randomized Parallel-Design Trial.

The aim of the study was to evaluate remission of type 2 diabetes following a short-term intervention with insulin glargine, sitagliptin/metformin, and lifestyle approaches. In this open multicenter trial, 102 patients with type 2 diabetes were randomized to 1) a 12-week intervention with sitagliptin/metformin, insulin glargine, and lifestyle therapy or 2) control group. Participants with HbA1c <7.3% (<56 mmol/mol) at 12 weeks were asked to stop diabetes medications and were followed for evidence of relapse over 52 weeks. Diabetes relapse criteria included HbA1c ≥6.5% (≥48 mmol/mol), ≥50% of capillary glucose readings >10 mmol/L over 1 week, and reinitiation of diabetes medications with or without abnormal fasting plasma glucose (FPG) or 2-h plasma glucose on an oral glucose tolerance test (OGTT). Time-to-relapse analysis was conducted to compare the treatment groups with (primary analysis) and without (supplementary analysis) FPG/OGTT relapse criteria. With the FPG/OGTT relapse criteria included, the hazard ratio (HR) of relapse was 0.72 (95% CI 0.47-1.10) in the intervention group compared with the control group (primary analysis), and the number of participants remaining in remission was not significantly different between treatment groups at 24, 36, 48, and 64 weeks. In the supplementary analyses without these criteria, HR of relapse was 0.60 (95% CI 0.39-0.95), and the number of participants remaining in remission was significantly higher (26 vs. 10%) in the intervention group at 36 weeks. Although our primary outcome was not statistically significant, the tested approach deserves further study with further optimization of its components.

Urban-suburban differences in the demographics and clinical profiles of type 2 diabetic patients attending primary healthcare centres in Malta.

Social factors might bring about health inequities. Vulnerable population groups, including those suffering from non-communicable diseases such as type 2 diabetes and depression, might be more prone to suffering the effects of such inequities. This study aimed to identify patients with type 2 diabetes with depression in a primary care setting, with the objective of describing health inequities among urban and suburban dwellers. A quantitative, retrospective and descriptive study was carried out among patients with diabetes attending public primary healthcare centres in different regions of Malta. Participants completed a self-administered questionnaire to identify patient and disease characteristics. Convenience sampling was used. The logistic regression model predicting the likelihood of different factors occurring with suburban patients with diabetes as opposed to those residing in urban areas contained five independent variables (severity of depression, monthly income, blood capillary glucose readings, weight and nationality). The full model containing all predictors was statistically significant, c2 (5, n=400), p<0.001, indicating that the model was able to distinguish between urban and suburban areas. The model as a whole explained between 10% (Cox and Snell R2) and 20% (Nagelkerke R2) of the variance in urban and suburban areas, and correctly classified 73.8% of cases. All five of the independent variables made a unique, statistically significant contribution to the model. Elevated blood glucose and obesity tended to be more prevalent in suburban respondents than in urban participants. Conversely, participants with diabetes living in urban areas were more likely to be depressed, non-Maltese and have a higher income. Despite the small size of the Maltese islands and the expected social homogeneity, health inequities still exist, highlighting the importance of social factors in the epidemiology of disease. This study provides information for healthcare professionals and policy-makers to mitigate the effects of social inequities on vulnerable population groups.

Detection accuracy of three glucose meters estimated by capillary blood glucose measurements compared with venous blood evaluated by the diabetes unit of the Hospital Evang&eacute;lico de Curitiba, Brazil

Detection accuracy of three glucose meters estimated by capillary blood glucose measurements compared with venous blood evaluated by the diabetes unit of the Hospital Evang&eacute;lico de Curitiba, Brazil Mirnaluci Paulino Ribeiro Gama, Camile Fiorese Cruzeta, Ana Carolina Ossowski, Marina Rech Bay, Mariella Muller Michaelis, St&ecirc;nio Lujan CamachoEndocrinology and Diabetes Service, Hospital Universit&aacute;rio Evang&eacute;lico de Curitiba, BrazilObjective: To compare capillary blood glucose measurements between three different glucose meters and with the serum glucose values of inpatients at the diabetes unit of Hospital Universit&aacute;rio Evang&eacute;lico de Curitiba, Brazil.Materials and methods: A total of 132 non-intensive care unit patients admitted for medical and surgical pathologies were evaluated. All patients reported a previous diagnosis of diabetes mellitus, were under 60 years of age, had no hematocrit alterations, remained hemodynamically stable during the time of data collection, and were given no ascorbic acid, acetaminophen, dopamine, or mannitol during follow-up. Capillary and serum blood glucose samples were collected simultaneously by finger-stick and venipuncture 2 hours after lunch, by the same observer, who was blinded to the serum glucose results. First, between July and November 2009, capillary glucose levels were measured using the blood glucose meters OneTouch SureStep&reg; and MediSense Optium&reg;. Between November 2009 and February 2010, capillary blood glucose levels were measured on the glucose meters OneTouch SureStep and Optium Xceed&reg;. The capillary glucose readings were analyzed between meters and also in relation to the serum blood glucose values by the t-test for paired samples and the Mood two-sample test.Results: The patients&rsquo; mean age was 50.45 years. The blood glucose means obtained using the meters OneTouch SureStep, MediSense Optium, and Optium Xceed were, respectively, 183.87 mg/dL, 178.49 mg/dL, and 192.73 mg/dL, and the mean for the serum glucose values was 174.58 mg/dL. A significant difference was found between the capillary measurements taken by the glucose meters and the serum glucose measurements (P &lt; 0.05), and no significant interdevice difference was found. After stratification of the serum blood glucose values into two groups, below and above 180 mg/dL, the variance found for the glucose meter OneTouch SureStep was statistically greater (P = 0.03) in relation to the serum glucose levels above 180 mg/dL, which was not the case with the glucose meters MediSense Optium (P = 0.06) and Optium Xceed (P = 0.12). The percentage of capillary blood glucose values showing a variation of less than 20% compared with serum values was 64.94% for OneTouch SureStep, 47.83% for Medisense Optium, and 51.61% for Optium Xceed, when serum glucose was greater than 75 mg/dL.Conclusion: The glucose meters tested showed an adequate interdevice correlation in their capillary glucose readings, in addition to correlating with the serum glucose values (ie, if a blood glucose reading is high or low in one test, it is likely to be respectively high or low in another). The means for the capillary blood glucose readings, however, were significantly different from the mean serum glucose. When serum glucose was above 180 mg/dL, there was a greater variance in the capillary measurements on the glucose meter OneTouch SureStep, with less correlation with the serum blood glucose (P &lt; 0.05), which did not occur significantly with the two other glucose meters. On the other hand, OneTouch SureStep had the highest accuracy in relation to serum glucose when the whole sample of serum glucose values above 75 mg/dL was analyzed, considering a variation of less than 20% in the measurements. The three glucose meters provide readings that correlate with the serum glucose values of hospitalized patients. However, one should bear in mind that capillary measurements quite often show more than a 20% variation in relation to serum glucose values, and caution should be exercised in interpreting the readings when serum glucose levels are elevated.Keywords: capillary blood glucose, serum glucose, glucose meters, hospitalized patients

Statistical Hypoglycemia Prediction

Hypoglycemia presents a significant risk for patients with insulin-dependent diabetes mellitus. We propose a predictive hypoglycemia detection algorithm that uses continuous glucose monitor (CGM) data with explicit certainty measures to enable early corrective action. The algorithm uses multiple statistical linear predictions with regression windows between 5 and 75 minutes and prediction horizons of 0 to 20 minutes. The regressions provide standard deviations, which are mapped to predictive error distributions using their averaged statistical correlation. These error distributions give confidence levels that the CGM reading will drop below a hypoglycemic threshold. An alarm is generated if the resultant probability of hypoglycemia from our predictions rises above an appropriate, user-settable value. This level trades off the positive predictive value against lead time and missed events. The algorithm was evaluated using data from 26 inpatient admissions of Navigator(R) 1-minute readings obtained as part of a DirecNet study. CGM readings were postprocessed to remove dropouts and calibrate against finger stick measurements. With a confidence threshold set to provide alarms that correspond to hypoglycemic events 60% of the time, our results were (1) a 23-minute mean lead time, (2) false positives averaging a lowest blood glucose value of 97 mg/dl, and (3) no missed hypoglycemic events, as defined by CGM readings. Using linearly interpolated FreeStyle capillary glucose readings to define hypoglycemic events provided (1) the lead time was 17 minutes, (2) the lowest mean glucose with false alarms was 100 mg/dl, and (3) no hypoglycemic events were missed. Statistical linear prediction gives significant lead time before hypoglycemic events with an explicit, tunable trade-off between longer lead times and fewer missed events versus fewer false alarms.

Real-Time Continuous Glucose Monitoring Together with Telemedical Assistance Improves Glycemic Control and Glucose Stability in Pump-Treated Patients

Real-time continuous glucose monitoring (CGM) has recently been incorporated into routine diabetes management because of the potential advantages it offers for glycemic control. The aim of our study was to evaluate the impact of the use of real-time CGM together with a telemedicine system in hemoglobin A1c and glucose variability in patients with type 1 diabetes treated with insulin pumps. Ten patients (five women, 41.2 [range, 21-62] years old, duration of diabetes 14.9 [range, 3-52] years) were included in this randomized crossover study. Patients used the DIABTel telemedicine system throughout the study, and real-time CGM was used for 3 days every week during the intervention phase. At the end of the control phase, a blind 3-day CGM was performed. Glucose variability was evaluated using the Glucose Risk Index (GRI), a comparative analysis of continuous glucose values over two consecutive hours. Hemoglobin A1c decreased significantly (8.1 +/- 1.1% vs. 7.3 +/- 0.8%; P = 0.007) after the intervention phase, while no changes were observed during the control phase. The mean number of daily capillary glucose readings was higher during the intervention phase (4.7 +/- 1.1 vs. 3.8 +/- 1.0; P < 0.01), because of an increase in random analyses (1.22 +/- 0.3 vs. 0.58 +/- 0.1; P < 0.01), and there was also a significant increase in the mean number of bolus doses per day (5.23 +/- 1.1 vs. 4.4 +/- 0.8; P < 0.05). The GRI was higher during the control phase than during the experimental phase (9.6 vs. 6.25; P < 0.05). Real-time CGM in conjunction with the DIABTel system improves glycemic control and glucose stability in pump-treated patients with type 1 diabetes.

What glucose target should we aim for in myocardial infarction?

Hyperglycaemia in the period following myocardial infarction is associated with increased mortality and there is some evidence that its treatment can improve survival. However, it remains unclear as to what the ideal glucose targets might be. This study examined observational data taken from a previously reported randomised controlled trial of insulin therapy for myocardial infarction (The Hyperglycaemia: Intensive Insulin Infusion In Infarction Study), to determine optimal glucose levels for this period. Capillary glucose readings were recorded at 8 standard time points for 234 subjects in first 24 h after myocardial infarction. Survival over 6 months was analysed according to whether 80% of each subject's glucose readings were below specified glucose thresholds (Achievers) or not (Non-Achievers). We found that the glucose threshold at which there was greatest separation in mortality between Achievers and Non-Achievers was at 8 mmol/L [144 mg/dL] (6 month mortality 1.6% vs. 9.1%, p = 0.05). Therefore subjects who maintained the majority of their blood glucose levels below 8 mmol/L following myocardial infarction had optimal survival outcomes. We suggest that this might be an appropriate glucose target to aim for in the peri-infarct period.

Glycemia Treatment Strategies in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial

There is an independent progressive epidemiologic relation between glycemia and cardiovascular disease (CVD) events; however, whether lowering glucose levels with currently available therapies can reduce CVD events remains unknown. The Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial is designed to answer this question in high-risk patients with type 2 diabetes mellitus. In ACCORD, 10,251 patients with type 2 diabetes and other CVD risk factors or CVD were randomly allocated to intensive glycemic control, targeting a glycosylated hemoglobin (HbA1c) level <6%, or standard glycemic control, targeting an HbA1c level of 7.0%-7.9%. All participants are provided with diabetes education, glucose-monitoring equipment, and antidiabetic medications. All participants in the intensive glycemic control group are started on > or = 2 classes of agents. Doses are intensified or a new medication class is added every month if HbA1c levels are > or = 6% or if >50% of premeal or postmeal capillary glucose readings are >5.6 mmol/L (100 mg/dL) or >7.8 mmol/L (140 mg/dL), respectively. All drug combinations are permitted, and drugs are reduced only because of side effects or contraindications. Annual training, menus of approaches for intensification, regular electronic messaging, audits of achieved glycemia, and central feedback to sites support glycemic intensification strategies in intensive participants. In participants in the standard glycemic control group, therapy is intensified whenever HbA1c is > or = 8%, and antihyperglycemic drugs that promote hypoglycemia (ie, insulin or insulin secretagogues) are reduced if HbA1c persistently decreases to <7% in the setting of hypoglycemia. ACCORD addresses the hypothesis that aggressive glucose lowering prevents CVD events in patients with type 2 diabetes. It is focused on the levels of glycemia achieved using a variety of strategies, not on the specific therapies used. It will also provide information on how to safely approach near-normal levels of glucose control in clinical practice and evidence to support future clinical guidelines for diabetes management in older adults.

A patient with confusing symptoms

A 48 year old woman presented to her general practitioner with a 16 month history of her mouth and fingers going numb and tingly. She also complained of feeling vacant and mentally detached. She reported numerous episodes of wandering, confusion, repeating words inappropriately, looking vacant, and not responding. All these events were witnessed by her children, but she had no recollection of them. All her symptoms were improved on eating. She was otherwise well, with no clinical features of Addison's disease, no past medical history of note, and was on no regular medication other than oestrogen implants. Home capillary glucose readings were 3.2 mmol/l, 2.7 mmol/l, 2.7 mmol/l, and 1.2 mmol/l (reference range 4-8 mmol/l). She was admitted for an overnight fast and was found to be completely unrousable by nursing staff in the morning. 1. What are the causes of hypoglycaemia? 2. What structure is seen on the computed tomography scan (line), and what is the abnormality (arrow)? 3. What does the histology image (figure 2) show? 4. What is the most likely diagnosis? 5. What is c peptide and what is its role in the diagnosis of hypoglycaemia? 1. A. Exogenous drugs—for example, insulin, oral hypoglycaemics, alcohol. B. Adrenal insufficiency or hypopituitarism. C. Liver failure. D. Islet cell tumour. E. Non-pancreatic neoplasm. F. Reactive …

Perioperative glycemic control and the risk of infectious complications in a cohort of adults with diabetes.

Although hyperglycemia is hypothesized to increase the short-term risk of infection, this hypothesis has not been well tested in a clinical setting. This study was designed to assess the relationship of perioperative glycemic control to the subsequent risk of infectious complications. A total of 411 adults with diabetes who underwent coronary artery surgery from 1990 to 1995 in the cardiac surgery service of an urban university hospital were included in a nonconcurrent prospective cohort study based on chart review. Perioperative glycemic control was characterized by the mean of six capillary glucose measurements taken during the 36-h interval following surgery. The major outcomes studied were infections of leg and chest wounds, pneumonia, and urinary tract infections. Mean postoperative glucose levels ranged from 121 to 352 mg/dl and were divided into quartiles: quartile 1 (121-206 mg/dl), quartile 2 (207-229 mg/dl), quartile 3 (230-252 mg/dl), and quartile 4 (253352 mg/dl). After simultaneous adjustment for age, sex, race, underlying comorbidity, acute severity of illness, and the length of the stay in the surgical intensive care unit, patients with higher mean capillary glucose readings were at increased risk of developing infections. Compared with people in the lowest quartile of postoperative glucose, those in quartiles 2 (relative odds of infection [95% CI] = 1.17 [0.57-2.40]), 3 (1.86 [0.94-3.68]), and 4 (1.78 [0.86-3.47]) were at progressively higher risk for infection (P = 0.05 for trend). In patients with diabetes who undergo coronary artery surgery, postoperative hyperglycemia is an independent predictor of short-term infectious complications. Physicians should consider a glucose concentration target of < or =200 mg/dl to reduce the risk of infection.