Self-monitoring Of Blood Glucose Measurements Research Articles

Differences Between Flash Glucose Monitor and Fingerprick Measurements.

Freestyle Libre (FL) is a factory calibrated Flash Glucose Monitor (FGM). We investigated Mean Absolute Relative Difference (MARD) between Self Monitoring of Blood Glucose (SMBG) and FL measurements in the first day of sensor wear in 39 subjects with Type 1 diabetes. The overall MARD was 12.3%, while the individual MARDs ranged from 4% to 25%. Five participants had a MARD ≥ 20%. We estimated bias and lag between the FL and SMBG measurements. The estimated biases range from −1.8 / to 1.4 /, and lags range from 2 to 24 . Bias is identified as a main cause of poor individual MARDs. The biases seem to persist in days 2–7 of sensor usage. All cases of MARD ≥ 20% in the first day are eliminated by bias correction, and overall MARD is reduced from 12.3% to 9.2%, indicating that adding support for voluntary user-supplied bias correction in the FL could improve its performance.

Accuracy of five systems for self-monitoring of blood glucose in the hands of adult lay-users and professionals applying ISO 15197:2013 accuracy criteria and potential insulin dosing errors

Objective: In this study, accuracy in the hands of intended users was evaluated for five self-monitoring of blood glucose (SMBG) systems based on ISO 15197:2013, and possibly related insulin dosing errors were calculated. In addition, accuracy was assessed in the hands of study personnel.Methods: For each system (Accu-Chek1 Aviva Connect [A], Contour2 Next One [B], FreeStyle Freedom Lite3 [C], GlucoMen4 areo [D] and OneTouch Verio5 [E]) one test strip lot was evaluated as required by ISO 15197:2013, clause 8. Number and percentage of SMBG measurements within ±15 mg/dl and ±15% of the comparison measurements at glucose concentrations <100 mg/dl and ≥100 mg/dl, respectively, were calculated. In addition, data is presented in surveillance error grids, and insulin dosing errors were modeled. The study was registered at ClinicalTrials.gov (NCT03033849).Results: Four systems (A, B, C, D) fulfilled the tested reagent system lot ISO 15197:2013 accuracy criteria with the tested reagent system lot with at least 95% (lay-users) and 99.5% (study personnel) of results within the defined limits. Measurements with all five systems were within the clinically acceptable zones of the consensus error grid and the surveillance error grid. Median modeled insulin dosing errors were between -0.8 and +0.6 units for measurements performed by lay-users and between -0.7 and +0.8 units for study personnel. Frequent lay-user errors were not checking the test strips’ expiry date, applying blood incorrectly and handling the device incorrectly.Conclusion: In this study, the systems showed slight differences in the number of results within ISO 15197:2013 accuracy limits. Inaccurate SMBG measurements can result in insulin dosing errors and adversely affect glycemic control.Trial registration: ClinicalTrials.gov identifier: NCT03033849.

Diabetes and Employment

Uncomplicated diabetes does not require any adjustment regarding employment, but those with complications should undergo detailed assessment to determine safety and effectiveness to perform duties. Though there is no such guidance in India, the American Diabetes Association (ADA) adopted a position statement that any person with diabetes, whether insulin treated or non-insulin treated, should be eligible for any employment for which he/she is otherwise qualified. Patients suffering from diabetes should be assessed individually, and after reviewing medical and treatment history, medical fitness to the job should be assigned. Maintenance of proper medical documentation and use of screening guidelines are a must. For this to be implemented properly, one needs state and national laws. A health care professional (HCP) treating the employee though preferred should have expertise in treating diabetes. If there is a disagreement between the opinions of physicians, an independent opinion from a HCP with clinical expertise in diabetes should be taken. An employer should not enquire about an employee’s condition till a job has been offered and can only do so if it is not safe or poses a threat to his health and also if expert opinion and medical documentation suggest so. Screening guidelines, though not used in India but regularly used in Western countries, can be used in evaluation. Safety risks should be assessed individually—recurrent hypoglycemia, not a single episode, may pose a risk whereas hyperglycemia and chronic complications though may not pose immediate risk should be assessed separately. Periodic safety assessments should be done. Jobs requiring operating firearms or running dangerous machinery may have safety concerns with patients having severe hypoglycemia or those on insulin or secretagogues. Hypoglycemia usually can be effectively prevented or self-treated by ingestion of glucose. Severe hypoglycemia requiring assistance may pose a risk; even if it is a single incidence, one has to be followed up properly and investigated to find out its cause. In recurrent severe hypoglycemia, as episodes cannot be explained, it is a risk for the employee himself as well as the public. Hyperglycemia leading to chronic complications is only relevant when it interferes with the performance in actual jobs. Self-monitored blood glucose measurements over a period of time give actual information and should be evaluated by a HCP with expertise in diabetes. Multiple incidents of severe hypoglycemia may pose a problem in high-risk occupations, and the factors responsible should be properly evaluated. Hypoglycemia unawareness increases the risk of a sudden episode of severe hypoglycemia and should be treated with changes in diabetes management. Chronic complications may pose a risk in some jobs, but if not present, possible future development should not be taken into consideration. The tools that do not accurately reflect the current state of diabetes like urine glucose and HbA1C should not be used. The term uncontrolled diabetes should also not be used as it is not well defined. A few accommodations are required at a job for diabetes patients to be able to perform their work responsibilities effectively and safely: testing blood glucose at regular intervals, administering insulin as and when required with proper storage facilities, access to snacks, and a flexible work schedule to accommodate needs and modifications if required for chronic complications.

User Performance Evaluation of Four Blood Glucose Monitoring Systems Applying ISO 15197:2013 Accuracy Criteria and Calculation of Insulin Dosing Errors.

IntroductionThe international standard ISO 15197:2013 requires a user performance evaluation to assess if intended users are able to obtain accurate blood glucose measurement results with a self-monitoring of blood glucose (SMBG) system. In this study, user performance was evaluated for four SMBG systems on the basis of ISO 15197:2013, and possibly related insulin dosing errors were calculated. Additionally, accuracy was assessed in the hands of study personnel.MethodsAccu-Chek® Performa Connect (A), Contour® plus ONE (B), FreeStyle Optium Neo (C), and OneTouch Select® Plus (D) were evaluated with one test strip lot. After familiarization with the systems, subjects collected a capillary blood sample and performed an SMBG measurement. Study personnel observed the subjects’ measurement technique. Then, study personnel performed SMBG measurements and comparison measurements. Number and percentage of SMBG measurements within ± 15 mg/dl and ± 15% of the comparison measurements at glucose concentrations < 100 and ≥ 100 mg/dl, respectively, were calculated. In addition, insulin dosing errors were modelled.ResultsIn the hands of lay-users three systems fulfilled ISO 15197:2013 accuracy criteria with the investigated test strip lot showing 96% (A), 100% (B), and 98% (C) of results within the defined limits. All systems fulfilled minimum accuracy criteria in the hands of study personnel [99% (A), 100% (B), 99.5% (C), 96% (D)]. Measurements with all four systems were within zones of the consensus error grid and surveillance error grid associated with no or minimal risk. Regarding calculated insulin dosing errors, all 99% ranges were between dosing errors of − 2.7 and + 1.4 units for measurements in the hands of lay-users and between − 2.5 and + 1.4 units for study personnel. Frequent lay-user errors were not checking the test strips’ expiry date and applying blood incorrectly.ConclusionsData obtained in this study show that not all available SMBG systems complied with ISO 15197:2013 accuracy criteria when measurements were performed by lay-users.Trial RegistrationThe study was registered at ClinicalTrials.gov (NCT02916576).FundingAscensia Diabetes Care Deutschland GmbH.Electronic supplementary materialThe online version of this article (10.1007/s13300-018-0392-6) contains supplementary material, which is available to authorized users.

Frequency of Self-Monitoring of Blood Glucose during the School Day Is Associated with the Optimal Glycemic Control among Korean Adolescents with Type 1 Diabetes

BackgroundThis study aimed to evaluate the relationship between the frequency of self-monitoring of blood glucose (SMBG) and glycosylated hemoglobin (HbA1c) levels among Korean adolescents with type 1 diabetes mellitus (T1DM). Factors affecting the SMBG frequency were analyzed in order to improve their glycemic control.MethodsSixty-one adolescents aged 13 to 18 years with T1DM were included from one tertiary center. Clinical and biochemical variables were recorded. Factors associated with SMBG frequency were assessed using structured self-reported questionnaires.ResultsAverage total daily SMBG frequency was 3.8±2.1 and frequency during the school day was 1.3±1.2. The mean HbA1c level was 8.6%±1.4%. As the daily SMBG frequency increased, HbA1c levels declined (P=0.001). The adjusted odds of achieving the target HbA1c in participants who performed daily SMBG ≥5 significantly increased 9.87 folds (95% confidence interval [CI], 1.58 to 61.70) compared with those performed SMBG four times a day. In the subjects whose SMBG frequency <1/day during the school day, an 80% reduction in the adjusted odds ratio 0.2 (95% CI, 0.05 to 0.86) showed compared to the group with performing two SMBG measurements in the school setting. The number of SMBG testing performed at school was significantly high for individuals assisted by their friends (P=0.031) and for those who did SMBG in the classrooms (P=0.039).ConclusionHigher SMBG frequency was significantly associated with lower HbA1c in Korean adolescents with T1DM. It would be necessary to establish the school environments that can facilitate adequate glycemic control, including frequent SMBG.

Self-measurement of Blood Glucose and Continuous Glucose Monitoring - Is There Only One Future?

Monitoring glycaemic control in patients with diabetes has evolved dramatically over the past decades. The introduction of easy-to-use systems for self-monitoring of blood glucose (SMBG) utilising capillary blood samples has resulted in the availability of a wide range of systems, providing different measurement quality. Systems for continuous glucose monitoring (CGM) – used mainly in patients with type 1 diabetes (T1D) – were made possible by the development of glucose sensors that measure glucose levels in the interstitial fluid (ISF) in the subcutaneous tissue of the skin. CGM readings might not correspond exactly to SMBG measurement results taken at the same time, especially during rapid changes in either blood glucose or ISF glucose levels. The mean absolute relative difference is the most popular method used for characterising the measurement performance of CGM systems. Unlike the International Organization for Standardization 15197:2013 criteria for SMBG systems, no accuracy standards for CGM systems exist. Measurement quality of CGM systems can vary based on several factors, limiting their safety and effective use in managing diabetes. Patients have to be trained adequately to make safe and efficient use of CGM systems (like with SMBG systems). Also, systems for CGM must be evaluated in terms of patient safety and the ability to provide accurate measurements regardless of the fluctuation of glucose levels. As new technological advancements in glucose monitoring are essential for improved management options of diabetes, such as automated insulin dosing systems, there is a need for a critical view of all such developments. It is likely that both, SMBG and CGM systems, will play important future roles in the treatment of diabetes.

Continuous Glucose Monitoring Effects on Blood Glucose Management in Diabetic Patients on Hemodialysis-Results in the Patients from Single Hospital

Objective: Diabetic patients on hemodialysis (HD) are prone to develop treatment-related serious hypoglycemia due to poor renal clearance of insulin and augmented drug efficacy, often resulting in withdrawal of insulin. Consequently, many patients are erroneously switched to oral glucose-lowering agents or diet therapy alone, without self-monitoring of blood glucose (SMBG). Therefore, we hypothesized that continuous glucose monitoring (CGM) may be useful for optimizing glycemic control and clinical management in diabetic patients on HD. Methods: In this study, 8 type 2 diabetic patients on HD who did not use SMBG after withdrawal of insulin and start of oral glucose-lowering agents, were recruited to measure and evaluate blood glucose with CGM. These patients thought to be controlled within glycemic control target proposed by the Japanese Society for Dialysis Therapy. Predialysis casual plasma glucose level (or 2-h postprandial plasma glucose level) of 200 mg/dl) after HD. Conclusions: Diabetic patients on HD require careful monitoring with SMBG, CGM, and direct measurement of postprandial blood glucose level during HD before any decision is made regarding withdrawal of insulin and cessation of SMBG.

Continuous glucose monitoring for patients with type 1 diabetes and impaired awareness of hypoglycaemia (IN CONTROL): a randomised, open-label, crossover trial

Patients with type 1 diabetes who have impaired awareness of hypoglycaemia have a three to six times increased risk of severe hypoglycaemia. We aimed to assess whether continuous glucose monitoring (CGM) improves glycaemia and prevents severe hypoglycaemia compared with self-monitoring of blood glucose (SMBG) in this high-risk population. We did a randomised, open-label, crossover trial (IN CONTROL) at two medical centres in the Netherlands. Eligible participants were patients diagnosed with type 1 diabetes according to American Diabetes Association criteria, aged 18-75 years, with impaired awareness of hypoglycaemia as confirmed by a Gold score of at least 4, and treated with either continuous subcutaneous insulin infusion or multiple daily insulin injections and doing at least three SMBG measurements per day. After screening, re-education about diabetes management, and a 6-week run-in phase (to obtain baseline CGM data), we randomly assigned patients (1:1) with a computer-generated allocation sequence (block size of four) to either 16 weeks of CGM followed by 12 weeks of washout and 16 weeks of SMBG, or 16 weeks of SMBG followed by 12 weeks of washout and 16 weeks of CGM (where the SMBG phase was the control). During the CGM phase, patients used a real-time CGM system consisting of a Paradigm Veo system with a MiniLink transmitter and an Enlite glucose sensor (Medtronic, CA, USA). During the SMBG phase, patients were equipped with a masked CGM device, consisting of an iPro 2 continuous glucose monitor and an Enlite glucose sensor, which does not display real-time glucose values. The number of SMBG measurements per day and SMBG systems were not standardised between patients, to mimic real-life conditions. During both intervention periods, patients attended follow-up visits at the centres each month and had telephone consultations 2 weeks after each visit inquiring about adverse events, episodes of hypoglycaemia, etc. The primary endpoint was the mean difference in percentage of time spent in normoglycaemia (4-10 mmol/L) over the total intervention periods, analysed on an intention-to-treat basis. Severe hypoglycaemia (requiring third party assistance) was a secondary endpoint. This trial is registered with ClinicalTrials.gov, number NCT01787903. Between March 4, 2013, and Feb 9, 2015, we recruited and randomly assigned 52 patients to either the CGM-SMBG sequence (n=26) or the SMBG-CGM sequence (n=26). The last patient visit was on March 21, 2016. Time spent in normoglycaemia was higher during CGM than during SMBG: 65·0% (95% CI 62·8-67·3) versus 55·4% (53·1-57·7; mean difference 9·6%, 95% CI 8·0-11·2; p<0·0001), with reductions in both time spent in hypoglycaemia (ie, blood glucose ≤3·9 mmol/L [6·8% vs 11·4%, mean difference 4·7%, 3·4-5·9; p<0·0001]) and time spent in hyperglycaemia (ie, blood glucose >10 mmol/L [28·2% vs 33·2%, mean difference 5·0%, 3·1-6·9; p<0·0001]). During CGM, the number of severe hypoglycaemic events was lower (14 events vs 34 events, p=0·033). Five serious adverse events other than severe hypoglycaemia occurred during the trial, but all were deemed unrelated to the trial intervention. Additionally, no mild to moderate adverse events were related to the trial intervention. CGM increased time spent in normoglycaemia and reduced severe hypoglycaemia in patients with type 1 diabetes and impaired awareness of hypoglycaemia, compared with SMBG. Our results support the concept of using CGM in this high-risk population. Eli Lilly and Sanofi.

Treatment intensification without improved HbA1c levels in children and adolescents with Type 1 diabetes mellitus.

To examine trends in diabetes treatment in Danish children and adolescents with Type 1 diabetes mellitus, comparing treatment intensity with metabolic outcomes in the population, and to describe the challenges of population-based registries in a clinical setting with rapidly changing treatment methods. This observational study is based on the Danish national population registry of childhood diabetes, which includes 99% of children diagnosed with Type 1 diabetes before the age of 15 years. We included 4527 people diagnosed between 2000 and 2012. Self-monitored blood glucose measurements, insulin injections/boluses, treatment method and metabolic control quantifications were analysed and adjusted for the effects of gender and ethnicity, the combined effect of age, visit year and duration, and for the random effects of individual and hospital settings. Treatment was intensified via an increasing number of self-monitored blood glucose measurements and injections/boluses. More than six injections/boluses and an increased number of self-monitored blood glucose measurements were significantly associated with lower metabolic control. No reduction, however, in the overall mean HbA1c concentration was observed between 2005 [66 mmol/mol (8.2%)] and 2012 [65 mmol/mol (8.1%)]. Changed registration practices in 2009 introduced artificial jumps in data. Intensifying treatment alone does not lead to improved metabolic control in the overall population despite the appearance of lower HbA1c in individuals with a greater number of self-monitored blood glucose measurements and injections/boluses. The contradictory results reflect difficulties in using observational studies to predict results of intervention in the individual. Data collected from population-based registries need to be adjusted continuously to reflect changes in care.

Self-monitoring of blood glucose measurements and glycaemic control in a managed care paediatric type 1 diabetes practice.

Intensive diabetes management requires intensive insulin treatment and self-monitoring of blood glucose (SMBG) measurements to obtain immediate information on the status of the blood glucose level and to obtain data for pattern analysis on which meal planning, insulin and lifestyle adjustments can be made. The value and optimal frequency of SMBGs are often questioned. To document the relationship between SMBG frequency and glycaemic control in a managed care paediatric type 1 diabetes practice. A retrospective analysis was performed on 141 managed care paediatric and adolescent patients over a 1-year period from 1 February 2010 to 30 January 2011. The patients were stratified according to their insulin regimen, frequency of SMBG was analysed, and glycaemic control was measured by glycated haemoglobin (HbA1c). The records of 141 paediatric and adolescent children aged 2 - 18 years were examined. A highly significant decrease (p<0.0001) in HbA1c was found when moving from two injections per day to three- and five-injection regimens. The average HbA1c and its variability reduced as the diabetes regimen became more intensive. A highly significant decrease (p<0.001) in HbA1c levels was detected as the frequency of SMBG increased, with an average decrease of 0.19% in HbA1c per unit increase in the number of SMBG measurements performed per day. The modal frequency of five SMBG measurements per day was required to achieve the American Diabetes Association and International Society for Pediatric and Adolescent Diabetes guideline recommended target HbA1c of <7.5% for a paediatric population. A beneficial relationship exists between frequency of SMBG and lower HbA1c in paediatric patients with type 1 diabetes.

Accuracy of devices for self-monitoring of blood glucose: A stochastic error model.

Self-monitoring of blood glucose (SMBG) devices are portable systems that allow measuring glucose concentration in a small drop of blood obtained via finger-prick. SMBG measurements are key in type 1 diabetes (T1D) management, e.g. for tuning insulin dosing. A reliable model of SMBG accuracy would be important in several applications, e.g. in in silico design and optimization of insulin therapy. In the literature, the most used model to describe SMBG error is the Gaussian distribution, which however is simplistic to properly account for the observed variability. Here, a methodology to derive a stochastic model of SMBG accuracy is presented. The method consists in dividing the glucose range into zones in which absolute/relative error presents constant standard deviation (SD) and, then, fitting by maximum-likelihood a skew-normal distribution model to absolute/relative error distribution in each zone. The method was tested on a database of SMBG measurements collected by the One Touch Ultra 2 (Lifescan Inc., Milpitas, CA). In particular, two zones were identified: zone 1 (BG≤75 mg/dl) with constant-SD absolute error and zone 2 (BG>75mg/dl) with constant-SD relative error. Mean and SD of the identified skew-normal distributions are, respectively, 2.03 and 6.51 in zone 1, 4.78% and 10.09% in zone 2. Visual predictive check validation showed that the derived two-zone model accurately reproduces SMBG measurement error distribution, performing significantly better than the single-zone Gaussian model used previously in the literature. This stochastic model allows a more realistic SMBG scenario for in silico design and optimization of T1D insulin therapy.

Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment.

In type 1 diabetes (T1D) therapy, continuous glucose monitoring (CGM) sensors, which provide glucose concentration in the subcutis every 1-5 min for 7 consecutive days, should allow in principle a more efficient insulin dosing than that based on the conventional 3-4 self-monitoring of blood glucose (SMBG) measurements per day. However, CGM, at variance with SMBG, is still not approved for insulin dosing in T1D management because regulatory agencies, e.g. FDA, are looking for more factual evidence on its safety. An in silico assessment of SMBG- vs CGM-driven insulin therapy can be a first step. Here we present a simulation model of T1D patient decision-making obtained by interconnecting models of glucose-insulin dynamics, SMBG and CGM measurement errors, carbohydrates-counting errors, insulin boluses time variability and forgetfulness, and subcutaneous insulin pump delivery. Inter- and intra- patient variability of model parameters are considered. The T1D patient decision-making model allows to run realistic multi-day simulations scenarios in a population of virtual subjects. We present the first results of simulations run in 20 virtual subjects over a 7-day period, which demonstrates that additional information brought by CGM (trend and hypo/hyperglycemic warnings) with respect to SMBG produces a statistically significant increment (about of 9%) of time spent by the patient in the euglycemic range (70-180 mg/dl).

Long-Term Home Study on Nocturnal Hypoglycemic Alarms Using a New Fully Implantable Continuous Glucose Monitoring System in Type 1 Diabetes.

This study analyzed the overall nocturnal performance during home use of a long-term subcutaneous implantable continuous glucose monitoring (CGM) sensor. In this study, 12 subjects with type 1 diabetes mellitus (T1DM) (mean±SD age, 37±8 years; mean±SD disease duration, 11±6 years) were implanted with an investigational continuous glucose sensor in the upper arm for up to 90 days. All subjects received full access to real-time glucose display and user programmable hypo- and hyperglycemic alarms. Subjects calibrated the sensors with a self-monitoring of blood glucose (SMBG) meter and continued to rely on their regular SMBG measurements for their diabetes management. Accuracy of the sensors during the home-use study was calculated using SMBG as the reference. The nocturnal sensor attenuation (NSA) concept was tested. Sensitivity and specificity of the nocturnal hypoglycemic alarm were calculated. Mean±SD glucose sensor life span was 87±7 days. The mean±SE absolute relative difference over the range of 40-400 mg/dL for the sensors in this home-use study was 12.3±0.7% using SMBG as the reference. The hypoglycemia alarms were set to be triggered when the glucose level went below 70 mg/dL. Percentage of nights with hypoglycemic alarms triggered for at least 10 min was 13.6%. Recovery into euglycemia within 30 min from the timestamp of the immediate confirmatory SMBG testing was obtained in 74% of all episodes (n=20). The implanted continuous glucose sensor showed a hypoglycemia detection sensitivity and specificity of 77% and 96%, respectively. The NSA-associated high negative rate of change of at least -4 mg/dL/min was not encountered during night use of the system. This home-use study of a fully implantable, long-term continuous glucose sensor shows excellent performance in nocturnal hypoglycemia detection in T1DM patients. The apparent lack of NSA affecting the implanted sensor and the high specificity of the hypoglycemic alarm expedite the recovery from nighttime hypoglycemia.

Defining the relationship between average glucose and HbA1c in patients with type 2 diabetes and chronic kidney disease

AimsTo examine the relationship between average glucose (AG) and HbA1c in patients with and without chronic kidney disease (CKD) and type 2 diabetes. Materials and methods43 patients with diabetes and CKD (stages 3–5) with stable glycaemic control, and glucose-lowering and erythropoiesis stimulating agent (ESA) doses, were prospectively studied for 3 months and compared to 104 age-matched controls with diabetes, without CKD from the ADAG study. Over 3 months, AG was calculated from 7 to 8 point self-monitored blood glucose measurements (SMBG) and from continuous glucose monitoring (CGMS), and mean HbA1c was calculated from 4 measurements. AG and HbA1c relationships were determined using multivariable linear regression analyses. ResultsThe CKD and non-CKD groups were well matched for age and gender. Mean AG tended to be higher (p=0.08) but HbA1c levels were similar (p=0.68) in the CKD compared with non-CKD groups. A linear relationship between AG and HbA1c was observed irrespective of the presence and stage of CKD. The relationship was weaker in patients with stage 4–5 CKD (non-CKD R2=0.75, stage 3 CKD R2=0.79 and stage 4–5 CKD R2=0.34, all p<0.01). The inclusion of ESA use in the model rendered the effect of CKD stage insignificant (R2=0.67, p<0.01). ConclusionsIn patients with type 2 diabetes and CKD there is a linear relationship between HbA1c and AG that is attenuated by ESA use, suggesting that ESA results in a systematic underestimation of AG derived from HbA1c.

Clinical impact of women with gestational diabetes mellitus by the new consensus criteria: two year experience in a single institution in Japan

There is a paucity of information on perinatal data regarding gestational diabetes mellitus (GDM) by the new criteria from a real experience because the number of health care associations implementing the new criteria is still limited. The aim of this study is to investigate perinatal features of the new criteria-defined GDM. We reviewed a total of 995 women with singleton pregnancy that underwent GDM screening followed by a diagnostic oral glucose tolerance test (OGTT). All women found to have GDM underwent self-monitoring of blood glucose measurements as well as dietary management. Insulin treatment was initiated when dietary treatment did not achieve the glycemic goal. Of the 995 women, 141 had GDM (14.2%): 104 with one, 27 with two, and 10 with three abnormal OGTT values. Women with two or three abnormal OGTT values (2/3-AV) needed insulin treatment more frequently than those with one abnormal OGTT value (1-AV) (70.3% vs 23.1%, P < 0.0001). After adjustment for age, pregravid overweight, gestational weeks at diagnosis, a first-degree family history of diabetes was correlated with the implementation of insulin treatment in women with 1-AV (adjusted odds ratio 3.9; 95% Confidence Interval 1.7-9.2; P = 0.001). When compared perinatal outcomes between women with normal glucose tolerance and GDM, fetal growth and the occurrence of pregnancy-induced hypertension were comparable between the two groups. Our data suggest that the IADPSG-defined GDM with 1-AV show less severe glucose intolerance, but might be at risk of insulin requirement when a first-degree family history of diabetes exists.

A cross‐sectional study of glycaemic control, complications and psychosocial functioning among 18‐ to 35‐year‐old adults with Type 1 diabetes

To describe the level of glycaemic control, complications and psychosocial functioning and the relationships between these variables in the under-researched group of younger adults with type 1 diabetes. Local electronic health records provided data on age, gender, disease duration, HbA1c and complications for 710 younger adults (18-35 years) with type 1 diabetes. A questionnaire with wide-ranging psychometric scales was used to measure various aspects of psychosocial functioning: the burden of diabetes-related problems, well-being, self-esteem, perceived competence in managing diabetes, perceived autonomy support from health professionals and self-management motivations. Furthermore, patients reported weekly self-monitored blood glucose measurements and insulin administration. Associations between HbA1c , complication and psychosocial indicators were tested using linear and logistic regression models, adjusted stepwise for confounders, including age, gender, diabetes duration, continuous subcutaneous insulin infusion, smoking and BMI. In total, 406 (57%) participants responded. The responders had a mean age of 27.1 (5.1) years, a mean diabetes duration of 13.5 (7.9) years and an HbA1c of 66 mmol/mol (8.2%), with similar values for both genders (P = 0.87). Complications were observed among women more commonly than among men (31.6 vs. 18.8%, P < 0.01), and high distress levels were more prevalent among women compared with men (51.2 vs. 31.9%, P < 0.0001). Except for perceived autonomy support, the psychosocial variables were all associated with HbA1c (P < 0.001). The high prevalence of poor glycaemic control, early complications and psychosocial distress require health-promoting interventions tailored to the interrelated clinical and psychosocial needs of younger adults with type 1 diabetes.

Evidence of a Strong Association Between Frequency of Self-Monitoring of Blood Glucose and Hemoglobin A1c Levels in T1D Exchange Clinic Registry Participants

OBJECTIVEDespite substantial evidence of the benefit of frequent self-monitoring of blood glucose (SMBG) in type 1 diabetes, certain insurers limit the number of test strips that they will provide. The large database of the T1D Exchange clinic registry provided an opportunity to evaluate the relationship between the number of SMBG measurements per day and HbA1c levels across a wide age range of children and adults.RESEARCH DESIGN AND METHODSThe analysis included 20,555 participants in the T1D Exchange clinic registry with type 1 diabetes ≥1 year and not using a continuous glucose monitor (11,641 younger than age 18 years and 8,914 18 years old or older). General linear models were used to assess the association between the number of SMBG measurements and HbA1c levels after adjusting for potential confounding variables.RESULTSA higher number of SMBG measurements per day were associated with non-Hispanic white race, insurance coverage, higher household income, and use of an insulin pump for insulin delivery (P < 0.001 for each factor). After adjusting for these factors, a higher number of SMBG measurements per day was strongly associated with a lower HbA1c level (adjusted P < 0.001), with the association being present in all age-groups and in both insulin pump and injection users.CONCLUSIONSThere is a strong association between higher SMBG frequency and lower HbA1c levels. It is important for insurers to consider that reducing restrictions on the number of test strips provided per month may lead to improved glycemic control for some patients with type 1 diabetes.

Self-Adjustment of Insulin Dose Using Graphically Depicted Self-Monitoring of Blood Glucose Measurements in Patients with Type 1 Diabetes Mellitus

There is a need for patients to be able to adjust their insulin doses accurately and independently during continuous subcutaneous insulin infusion (CSII) therapy in order to avoid glycemic excursions and improve glycemic control. Use of new technology has the potential to aid patients in visualizing their circadian patterns and improving their understanding of data provided by self-monitored blood glucose (SMBG) measurements. A 24-week crossover study was performed in 25 patients with type 1 diabetes mellitus using CSII and SMBG. Patients were randomized either to entering blood glucose data into handwritten logbooks or to using the Accu-Chek SmartPix information management system (IMS) coupled with instructions from a training manual to aid interpretation of the IMS readings. Patients analyzed these chart readings every 2 weeks, and outpatient visits were scheduled for both arms every 6 weeks. There was a significantly lower mean overall blood glucose level with the IMS compared with use of a logbook (139 ± 16.2 versus 150 ± 19.8 mg/dl; Δ = 10.8 mg/dl; p < .01), and a significantly higher proportion of blood glucose values was in the target range compared with use of a logbook (43.6% versus 38.5%; p < .001). Hypoglycemic events were also significantly lower with the IMS compared with logbooks (3.7 fewer events/6 weeks; p < .05). There was no significant difference between groups in the daily frequency of SMBG measurements. The use of an IMS, coupled with an easily understood training manual, enables patients to improve glycemic control by performing accurate and timely self-adjustments to their insulin regimens.

Self-monitoring of blood glucose

Self-monitoring of blood glucose

Impact of nocturnal hypoglycemic events on diabetes management, sleep quality, and next-day function: results from a four-country survey

Objectives:Non-severe nocturnal hypoglycemic events (NSNHEs) may have a major impact on patients. The objective was to determine how NSNHEs affect diabetes management, sleep quality, functioning, and to assess if these impacts differ by diabetes type or country.Methods:An internet survey to adults with diabetes in the US, UK, Germany, and France.Results:Of 6756 screened respondents, 1086 reported an NSNHE in the past month. For this last event, respondents with type 2 required significantly more time than type 1 to recognize and respond to the event (1.5 vs 1.1 hours), 25.7% (T1) and 18.5% (T2) decreased their normal insulin dose due to their most recent NSNHE. All respondents were likely to take 1–2 additional self-monitored blood glucose measurements on the day following. NSNHEs were associated with a high proportion of respondents contacting a healthcare professional (18.6% T1, 27.8% T2) reporting they could not return to sleep at night (13.3% T1, 13.4% T2), and tiredness on the day following the event (71.2% for both). Of the respondents working for pay, 18.4% T1 and 28.1% T2 reported being absent from work due to the NSNHE, and a substantial proportion of respondents (8.7% T1, 14.4% T2) also reported missing a meeting or work appointment or not finishing a task on time. Compared with other countries, respondents from France may experience a more substantial impact on diabetes management and daily functioning following an NSNHE. Potential limitations in this study include recall and selection bias; however, these biases are not believed to have impacted findings in any meaningful way.Conclusions:NSNHEs are associated with a substantial impact on diabetes management, sleep quality, and next-day functioning.