DIABETES TECHNOLOGY & THERAPEUTICS Volume 17, Supplement 1, 2015 ª Mary Ann Liebert, Inc. DOI: 10.1089/dia.2015.1501
ORIGINAL ARTICLE
Self-Monitoring of Blood Glucose Satish K. Garg1 and Irl B. Hirsch 2
Introduction
T
he role of self-monitoring of blood glucose (SMBG) in diabetes management continues to be debated especially for type 2 diabetes (T2D). Since continuous glucose monitoring (CGM) is only approved as adjunctive to SMBG, its role in self-management of type 1 diabetes (T1D) is at least noncontroversial. Most of the literature supports use of frequent SMBG in T1D for better glucose control. The controversy for SMBG use in T2D is partly due to continued advertisements of ‘‘no need of monitoring’’ by the industry that makes noninsulin products. It is true that if SMBG information is not used to adjust insulin dose or medication dose adjustments (that can be made every 3 months based on A1c values), the exact role of SMBG in T2D remains controversial. The other side of the coin is to detect glycemic patterns and hypoglycemia that may require early attention/therapeutic changes for better diabetes care in the early course of T2D rather than having to wait for a change in A1c values, which may take several months/years. The cost of meter strips has come down significantly to *$10.00 for a box of 50 strips at least in the United States as per ‘‘government mandate.’’ Emergence of generic strips and the reduction in the cost may have impacted the future development of more accurate meters/strips especially as mandated by the FDA (new ISO standards) that all meters must meet within 15% of the standard glucose values as highlighted in the 2013 yearbook. We discuss in this article the role of SMBG in T1D, T2D, and inpatients. The future may rely on the use and application of SMBG data for mobile applications to improve real-life diabetes outcomes.
and support. Blood glucose monitoring and patient education are essential in diabetes care and management, and if used appropriately, can help to achieve maximum benefit for the patient and diabetes care team. The link between blood glucose levels and the incidence of diabetes-related complications are considered in this study. The different blood glucose monitoring strategies, particularly self-monitoring of blood glucose in people with type 2 diabetes, are evaluated. The frequency of blood glucose monitoring and the identification of patterns and trends in blood glucose control are highlighted and applied to practice. Comment This article highlights the need and the value of SMBG in type 2 diabetes. More importantly, the article brings out its role for long-term complications of type 2 diabetes if glucose patterns are evaluated and necessary action is taken for therapeutic changes in time. A glucose meter evaluation co-designed with both health professional and consumer input Thompson H 1, Chan H 2, Logan FJ 2, Heenan HF 2, Taylor L 2, Murray C 2, Florkowski CM 3, Frampton CM 4, Lunt H 2 University of Otago, Christchurch, New Zealand; 2Diabetes Centre, Christchurch, New Zealand; 3Canterbury Health Laboratories, Christchurch, New Zealand; and 4 Department of Medicine, University of Otago, Christchurch, New Zealand
1
N Z Med J 2013; 126: 90–97
Blood glucose monitoring in diabetes Holt P
Introduction
School of Healthcare, University of Leeds, UK Nurs Stand 2014; 28: 52–58
Diabetes is one of the few chronic conditions that individuals can successfully manage and control on a day-to-day basis, providing that they have access to appropriate advice
Health consumers’ input into assessment of medical device safety is traditionally given either as part of study outcome (trial participants) or during post-marketing surveillance. Direct consumer input into the methodological design of device assessment is less common.
1
University of Colorado Health Sciences Center, Aurora, CO. University of Washington Medical Center, Seattle, WA.
2
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S-4 Methods In this study, the difference in requirements for assessment of a measuring device from the consumer and clinician perspectives, using the example of hand-held glucose meters, are reviewed. Around 80,000 New Zealanders with diabetes recently changed their glucose meter system to enable ongoing access to PHARMAC-subsidized meters and strips. Consumers were more interested in a direct comparison of their ‘‘old’’ meter system (Accu-Chek Performa) with their ‘‘new’’ meter system (CareSens brand, including the CareSens N POP), rather than comparisons against a laboratory standard.
GARG AND HIRSCH dynamic electrochemistry to correct for potential interferences and thereby minimize system errors. Research and Methods A single-center, in vitro diagnostic device performance evaluation with heparinized oxygenated venous blood samples (intra-assay precision) and control solutions (interassay precision) was performed in a laboratory setting, comparing BGStar and iBGStar with 12 competitors. The primary outcome was the coefficient of variation percent (CV%) of the BGMs investigated.
Results
Results
This direct comparison of meter/strip systems showed that the CareSens N POP meter read approximately 0.6 mmol/L higher than the Performa system.
In interassay precision analyses, all but GlucoMen LX had a CV < 5%, and in intra-assay precision analyses, 10 of the 14 devices tested had CV < 5%. BGStar and iBGStar had a CV < 5% in both the inter- and intra-assay precision analyses. The smallest variation was found in the near-normoglycemic glucose range (5.3–8.0 mmol/L) for both BGStar and iBGStar in the interassay precision analysis.
Conclusion While this difference is unlikely to result in major errors in clinical decision making such as major insulin dosing errors, this information is nevertheless of interest to consumers who switched meters so that they could maintain access to PHARMAC-subsidized meters and strips. We recommend that when practical, the consumer perspective be incorporated into study design related to medical device assessment. Comment This is an important study that evaluates patient’s response to a generic meter and strips in an attempt to reduce the cost to the health-care system in New Zealand. Even though the new meter/strips were reading glucose readings by about 10 mg/dL higher than the standard Accu-Chek meter, this difference is unlikely to impact ongoing diabetes care by the patients. I agree with the authors’ conclusions that going forward patients’ perspectives may need to be evaluated while determining efficacy of the new meters/strips system rather than doing the traditional study of comparing with Yellow Springs Instruments or the auto-analyzer. The precision study: examining the interand intra-assay variability of replicate measurements of BGStar, iBGStar, and 12 other blood glucose monitors
Conclusions BGStar and iBGStar were proven to have very good interassay and high intra-assay precision, demonstrating low scattering of replicate measurements with both clinical samples and control solutions. Comment Here is an example of an industry-sponsored study showing that the iBGStar had the lowest CV in both inter- and intra-assay precision analysis. Such studies should ideally be done without any industry bias and in an academic setting, since we are likely to see many new meter/strip systems designed for patient use in a more cost-effective way. Fasting glucose level is associated with nocturnal hypoglycemia in elderly male patients with type 2 diabetes Fang F, Xiao H, Li C, Tian H, Li J, Li Z, Cheng X Department of Geriatric Endocrinology, Chinese PLA General Hospital, Beijing, PR China
Ramljak S1, Musholt PB 1, Schipper C 1, Flacke F 2, Sieber J 2, Borchert M 3, Forst T1, Pfu¨tzner A 1
Aging Male 2013; 16: 132–36
1
Background
Expert Opin Med Diagn 2013; 7: 511–16
Nocturnal hypoglycemia is a common and serious problem among patients with type 2 diabetes (T2DM), especially in the elderly. This study investigated whether fasting glucose is an indicator of nocturnal hypoglycemia in elderly male patients with T2DM.
IKFE–Institute for Clinical Research and Development, Mainz, Germany; and 2Sanofi, Frankfurt, Germany; 3IKFE CRO, Mainz, Germany
Objective Self-monitoring of blood glucose is a key element in diabetes management. Accurate and precise performance of blood glucose monitors (BGMs) ensures that valid values are obtained to guide treatment decisions by patients and physicians. BGStar and iBGStar are hand-held BGMs that use
Methods A total of 291 elderly male patients with type 2 diabetes who received continuous glucose monitoring (CGM) between January 2007 and January 2011 were enrolled in the
SELF-MONITORING OF BLOOD GLUCOSE study. The association of fasting glucose and nocturnal hypoglycemia based on CGM data was analyzed, comparing with bedtime glucose. Results Based on CGM data, patients with nocturnal hypoglycemia had significantly lower fasting glucose (5.88 – 1.29 vs. 6.92 – 1.32 mmol/L) and bedtime glucose (7.33 – 1.70 vs. 8.01 – 1.95 mmol/L) than patients without nocturnal hypoglycemia (both p < 0.01). Compared with the highest quartile, the lowest quartile of fasting glucose had a significantly increased risk of nocturnal hypoglycemia after the multiple adjustments ( p for trend < 0.001). However, this association did not appear in bedtime glucose. When predicting nocturnal hypoglycemia either by fasting glucose or bedtime glucose using the area under receiver operating characteristic (ROC) curve, fasting glucose, but not bedtime glucose, was an indicator of nocturnal hypoglycemia, with an area under the ROC curve (AUC) of 0.714 (95% CI: 0.653–0.774, p < 0.001). On the ROC curve, the Youden index was maximal when fasting glucose was 6.1 mmol/L.
S-5 Italy; 5Department of Internal Medicine, University of Turin, Turin, Italy; 6Division of Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Padova, Padua, Italy; 7Diabetes Unit, Ospedale Madonna del Soccorso, S. Benedetto del Tronto, Italy; 8Medical Department Roche S.p.A, Monza, Italy; 9Medical Affairs Department Roche Diagnostics S.p.A., Monza, Italy; 10Information and Education Development, CGParkin, Inc., Las Vegas, NV; 11Section of Medical Statistics and Biometry GA Maccacaro, Department of Occupational Health Clinica del Lavoro L Devoto, School of Medicine, University of Milan, Milan, Italy; and 12Department of Internal Medicine, Policlinico Universitario Gaetano Martino, Messina, Italy Acta Diabetol 2013; 50: 663–72
Introduction Self-monitoring of blood glucose (SMBG) is a core component of diabetes management. However, the International Diabetes Federation recommends that SMBG be performed in a structured manner and that the data are accurately interpreted and used to take appropriate therapeutic actions.
Conclusion
Design and Methods
Fasting glucose may be a convenient and clinically useful indicator of nocturnal hypoglycemia in elderly male patients with T2DM. Risk of nocturnal hypoglycemia significantly increased when fasting glucose was less than 6.1 mmol/L.
We designed a study to evaluate the impact of structured SMBG on glycemic control in non-insulin-treated type 2 diabetes (T2DM) patients. The Prospective, Randomized Trial on Intensive SMBG Management Added Value in Non-InsulinTreated T2DM Patients (PRISMA) is a 12-month, prospective, multicenter, open, parallel-group, randomized, and controlled trial to evaluate the added value of an intensive, structured SMBG regimen in T2DM patients treated with oral agents and/ or diet. One thousand patients (500 per arm) will be enrolled at 39 clinical sites in Italy. Eligible patients will be randomized to the intensive structured monitoring (ISM) group or the active control (AC) group, with a glycosylated hemoglobin (HbA1c) target of < 7.0%. Intervention will comprise (a) structured SMBG (4-point daily glucose profiles on 3 days per week [ISM]; discretionary, unstructured SMBG [AC]); (b) comprehensive patient education (both groups); and (c) clinician’s adjustment of diabetes medications using an algorithm targeting SMBG levels, HbA1c and hypoglycemia (ISM) or HbA1c and hypoglycemia (AC).
Comment Severe hypoglycemia is an important problem in the elderly on insulin therapy with type 1 and type 2 diabetes, especially because of hypoglycemic unawareness and altered cognitive abilities due to long-term duration of diabetes. This continues to be the leading cause of increased hospital admissions in the United States. Thus, the new technology use in this population might prevent unnecessary hospitalizations, reduce healthcare costs, and improve overall quality of life. The above study highlights the role of CGM, especially the glucose values (less than 6.1 mmol/L), in the fasting state that determine the high risk of nocturnal hypoglycemia. Prospective, randomized trial on intensive SMBG management added value in non-insulin-treated T2DM patients (PRISMA): a study to determine the effect of a structured SMBG intervention Scavini M 1, Bosi E 1,2, Ceriello A 3, Giorgino F 4, Porta M 5, Tiengo A 6, Vespasiani G 7, Bottalico D 8, Marino R 9, Parkin C 10, Bonizzoni E 11, Cucinotta D 12 1
Diabetes Research Institute, San Raffaele Scientific Institute, Milan, Italy; 2San Raffaele Vita-Salute University, Milan, Italy; 3Institut d’Investigacions Biome`diques August Pi Sunyer (IDIBAPS) and Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadis (CIBERDEM), Barcelona, Spain; 4Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari School of Medicine, Bari,
Conclusion The intervention and trial design will build upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of perprotocol and intent-to-treat analyses facilitates assessment of the intervention. Inclusion of multiple dependent variables allows a broader impact assessment of the intervention, including changes in patient and physician attitudes and behaviors. Intensive structured self-monitoring of blood glucose and glycemic control in non-insulintreated type 2 diabetes: the PRISMA randomized trial Bosi E 1,2, Scavini M 1,2, Ceriello A 3, Cucinotta D 4, Tiengo A 5, Marino R 6, Bonizzoni E 7, Giorgino F 8; PRISMA Study Group
S-6 1
Diabetes Research Institute, San Raffaele Hospital and Scientific Institute, Milan, Italy; 2San Raffaele Vita-Salute University, Milan, Italy; 3Institut d’Investigacions Biome`diques August Pi Sunyer and Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadis, Barcelona, Spain; 4Department of Internal Medicine, Policlinico Universitario Gaetano Martino, Messina, Italy; 5Division of Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Padova, Padova, Italy; 6Medical Affairs, Roche Diagnostics, Monza, Italy; 7 Section of Medical Statistics and Biometry G.A. Maccacaro, Department of Occupational Health Clinica del Lavoro L. Devoto, School of Medicine, University of Milan, Milan, Italy; and 8Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari School of Medicine, Bari, Italy Diabetes Care 2013; 36: 2887–94 Comment in: Diabetes Care 2013; 36: e217; Diabetes Care 2013; 36: e218
Objective
GARG AND HIRSCH Self-monitoring of blood glucose in type 2 diabetes: patients’ perceptions of ‘‘high’’ readings Evans JM1, Mackison D 1, Swanson V 2, Donnan PT 3, Emslie-Smith A 4, Lawton J 5 1
School of Nursing, Midwifery and Health, University of Stirling, Scotland, UK; 2School of Natural Sciences, University of Stirling, Scotland, UK; 3Dundee Epidemiology and Biostatistics Unit, Division of Population Health Sciences, Medical Research Institute, University of Dundee, Scotland, UK; 4The Mill Practice, Dundee, Scotland, UK; and 5Centre for Population Health Sciences, University of Edinburgh, Scotland, UK
Diabetes Res Clin Pract 2013; 102: e5–7
Among 207 non-insulin-using patients with type 2 diabetes in Tayside, Scotland, who self-monitored blood glucose, we present evidence that many are tolerant of higher blood glucose levels than are clinically advisable. This may explain the lack of empirical evidence for the clinical benefits of selfmonitoring in this group. Comment The above four studies highlight the importance of SMBG in type 2 diabetes. The PRISMA study published earlier highlights the importance of structured SMBG monitoring for patients with type 2 diabetes. The other study highlights the patients’ perceptions of high readings. Patients are usually more tolerant of higher blood glucose values than advisable, and thus the exact role of SMBG in type 2 diabetes may be difficult to evaluate in real life.
The added value of intensive self-monitoring of blood glucose (SMBG), structured in timing and frequency, in noninsulin-treated patients with type 2 diabetes was evaluated. Research Design and Methods The 12-month, randomized, clinical trial enrolled 1,024 patients with non-insulin-treated type 2 diabetes (median baseline HbA1c, 7.3% [IQR, 6.9–7.8%]) at 39 diabetes clinics in Italy. After standardized education, 501 patients were randomized to intensive structured monitoring (ISM) with 4-point glycemic profiles (fasting, preprandial, 2 h postprandial, and postabsorptive measurements) performed 3 days/week; 523 patients were randomized to active control (AC) with 4-point glycemic profiles performed at baseline and at 6 and 12 months. Two primary end points were tested in hierarchical order: HbA1c change at 12 months and percentage of patients at risk target for low and high blood glucose index. Results Intent-to-treat analysis showed greater HbA1c reductions over 12 months in ISM ( - 0.39%) than in AC patients ( - 0.27%), with a between-group difference of - 0.12% (95% CI, - 0.210 to - 0.024; p = 0.013). In the per-protocol analysis, the betweengroup difference was - 0.21% ( - 0.331 to - 0.089; p = 0.0007). More ISM than AC patients achieved clinically meaningful reductions in HbA1c ( > 0.3%, > 0.4%, or > 0.5%) at study end ( p < 0.025). The proportion of patients reaching/maintaining the risk target at month 12 was similar in ISM (74.6%) and AC (70.1%) patients ( p = 0.131). At visits 2, 3, and 4, diabetes medications were changed more often in ISM than in AC patients ( p < 0.001). Conclusion Use of structured SMBG improves glycemic control and provides guidance in prescribing diabetes medications in patients with relatively well-controlled non-insulin-treated type 2 diabetes.
Determinants of self-monitoring of blood glucose in patients with type 1 diabetes: a multicenter study in Brazil Gomes MB1, Tannus LR 1, Cobas RA 1, Matheus AS 1, Dualib P 2,3, Zucatti AT 3, Cani C 4, Guedes AD 5, Santos FM 6, Sepulveda J 7, Tolentino M 8, Fac¸anha MC 9, Faria AC 10, Lavigne S11, Montenegro AP 12, Rodacki M 13, de Fatima Guedes M 14, Szundy R 13, Cordeiro MM15, Santos PT 16, Negrato CA 14; Brazilian Type 1 Diabetes Study Group (BrazDiab1SG) 1
Diabetes Unit, Department of Internal Medicine, State University Hospital of Rio de Janeiro, Sa˜o Paulo, Brazil; 2 Diabetes Unit, Federal University of Sa˜o Paulo State, Sa˜o Paulo, Brazil; 3Federal University Hospital of Porto Alegre, Rio Grande do Sul, Brazil; 4Diabetes Unit, University Hospital of Sa˜o Paulo, Sa˜o Paulo, Brazil; 5Centro de Diabetes do Estado da Bahia, Para´, Brazil; 6Federal University Hospital Joa˜o Barreto, Para´, Brazil; 7Endocrinology Unit, Santa Casa Hospital of Belo Horizonte, Minas Gerais, Brazil; 8Taguatinga Regional Hospital, Brası´lia, Brazil; 9 Diabetes and Hypertension Research Center, Federal University of Ceara´, Ceara´, Brazil; 10Federal University Hospital of Parana´, Parana´, Brazil; 11Instituto da Crianc¸a com Diabete Rio Grande Sul, Ceara´, Brazil; 12Federal University of Ceara´, Ceara´, Brazil; 13Federal University Hospital of Rio de Janeiro, Rio de Janeiro, Brazil;
SELF-MONITORING OF BLOOD GLUCOSE 14
Bauru’s Diabetics Association, Department of Internal Medicine, Bauru, Sa˜o Paulo, Brazil; 15General Hospital of Bonsucesso, Rio de Janeiro, Brazil; and 16Genetic Department National Institute of Cancer, Hospital of Bonsucesso, Bonsucesso, Brazil Diabetic Med 2013; 30: 1255–62
S-7 Objective To determine whether personality traits (conscientiousness, agreeableness, emotional regulation, extraversion, and openness to experience) are associated with glycemic control and blood glucose monitoring behavior, and change or stability of these outcomes over time, in young people with type 1 diabetes.
Aim This study determined the relationship between the daily frequency of self-monitoring of blood glucose and glycemic control, and demographic and socioeconomic status in patients with type 1 diabetes under routine clinical care in Brazil. Methods A cross-sectional, multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,176 patients, aged 22 – 11.8 years, of whom 56.3% were female and 57.4% were Caucasian. The mean time since diabetes diagnosis was 11.7 – 8.1 years. Results The prevalence of self-monitoring of blood glucose was 88.5%. There was a significant increase in self-monitoring frequency associated with female gender, lower ages, more intensive diabetes management, and higher socioeconomic status. A correlation between HbA1c levels and the daily frequency of self-monitoring was observed [r(s) = - 0.13; p = 0.001]. The mean HbA1c levels were related to the daily frequency of self-monitoring ( p < 0.001) without additional benefit to patients who performed self-monitoring more than four times daily (9.2%, 11.2%, 10.2%, 15.2%, and 15% for one, two, three, four, five, or more self-monitoring tests daily, respectively; p < 0.0001). Conclusion The majority of our patients (88.5%) performed three or more self-monitoring tests daily, with more frequent testing reported by females, younger patients, and those on intensive insulin regimens and of higher socioeconomic status. No additional benefit was found in patients who performed selfmonitoring more than four times daily. The diabetes care team must improve patients’ education regarding selfmonitoring of blood glucose and its benefits. Glycemic control and blood glucose monitoring over time in a sample of young Australians with type 1 diabetes: the role of personality Waller D 1, Johnston C 1, Molyneaux L 2, Brown-Singh L1, Hatherly K 3, Smith L 3, Overland J 2,4 1
School of Education, University of Western Sydney, Penrith, New South Wales, Australia; 2Diabetes Centre, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia; and 3Faculty of Pharmacy and 4Sydney School of Nursing, University of Sydney, Sydney, New South Wales, Australia
Diabetes Care 2013; 36: 2968–73
Methods A 3-year longitudinal study was conducted using data from 142 individuals with type 1 diabetes, 8–19 years of age. Personality was assessed at baseline using the Five-Factor Personality Inventory for Children. Data relating to glycemic control (HbA1c) and frequency of blood glucose monitoring (based on meter memory) were collected annually. Relationships between personality traits and HbA1c and monitoring frequency were examined using regression analysis and mixed-design ANOVA. Results Three of the Five-Factor domains were independently associated with glycemic control. Individuals high in conscientiousness and agreeableness had a lower and more stable HbA1c across the 3-year study period. In contrast, the HbA1c of individuals scoring low on these traits was either consistently worse or deteriorated over time. Low or high emotional regulation scores were also associated with worse glycemic control. By the third year, these domains, together with initial HbA1c, accounted for 39% of HbA1c variance. Conscientiousness was the only personality factor associated with blood glucose monitoring behavior. Conclusion Results of this study underline the importance of personality in contributing to diabetes outcomes. Attention to a young person’s personality, and appropriate tailoring of diabetes management to ensure an individualized approach, may help to optimize diabetes outcomes. Comment The above two studies document the importance of personality and the role of frequent glucose monitoring in type 1 diabetes. The type 1 Diabetes Exchange data from the United States that include more than 25,000 patients from 70 leading centers in the United States concluded that frequent glucose monitoring (SMBG) was associated with lowered A1c values in a crosssectional real-life study. The drop in A1c was proportional to the frequency of glucose monitoring. On the contrary, the above study from Brazil found no additional benefit from SMBG if performed more than four times a day. This was also a real-life study; however, the sample size was much smaller as compared to the type 1 Diabetes Exchange data. The authors do conclude that better education is needed for improving outcomes in patients with type 1 diabetes.
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GARG AND HIRSCH
SMBG out of control: the need for educating patients about control solution
Aims
This project was conducted to determine how prevalent control solution calibration is in patients who perform selfmonitoring of blood glucose (SMBG).
The Somogyi effect postulates that nocturnal hypoglycemia causes fasting hyperglycemia attributable to counterregulatory hormone release (although most published evidence failed to support this hypothesis). This concept remains firmly embedded in clinical practice and often prevents patients and professionals from optimizing overnight insulin. Previous observational data found that lower fasting glucose was associated with nocturnal hypoglycemia, but did not assess the probability of infrequent individual episodes of rebound hypoglycemia. Continuous glucose monitoring data were analyzed to explore its prevalence.
Methods
Methods
Eighteen patients with or parents of children with type 1 diabetes mellitus were surveyed to gauge patients’ knowledge of control testing and the prevalence of its use. U.S. census data on educational attainment of residents in the surveyed region were used. The availability of control solution (CS) in all pharmacies in eight cities in mid–San Mateo County, California, was evaluated as well. User manuals from six leading blood glucose monitor (BGM) manufacturers were retrieved for their indications for using CS.
Data from 89 patients with type 1 diabetes who participated in the UK hypoglycemia study were analyzed. Fasting capillary glucose following nights with and without nocturnal hypoglycemia (sensor glucose < 3.5 mmol/L) were compared.
Chaudhry T, Klonoff DC Diabetes Research Institute, Services, San Mateo, CA
Mills-Peninsula
Health
Diabetes Educ 2013; 39: 689–95
Purpose
Results It was found that although 82% of respondents claimed to know what CS is, 58% claimed to never use this product. In the geographic region analyzed, the educational attainment was above the educational level for the entire San Francisco Bay Area and the United States. CS in our region was stocked by only 15% of pharmacies that sold BGM equipment, even though 6 major BGM manufacturers in the aggregate listed 10 indications for its use. Conclusions BGM users are frequently not using CS to calibrate their monitors. The low availability of CS at pharmacies might contribute to the low demand for this product. Patients who perform SMBG need education from diabetes educators about proper CS calibration. Without the use of CS, BGMs are not being used according to manufacturer’s specifications. This misuse could lead to erroneous results and erode the potential benefits of SMBG. Comment This has been a topic that has had minimal visibility, compared to the industry’s ability to provide ‘‘no-code’’ strips. One has to wonder how accuracy would improve if CS was more uniformly used as instructed by the manufacturers. Do high fasting glucose levels suggest nocturnal hypoglycemia? The Somogyi effect—more fiction than fact? Choudhary P, Davies C, Emery CJ, Heller SR Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, UK Diabetic Med 2013; 30: 914–17 Comment in: Diabetic Med 2013; 30: 889–90
Results Fasting capillary blood glucose was lower after nights with hypoglycemia than without [5.5 (3.0) vs. 14.5 (4.5) mmol/L, p < 0.0001], and was lower on nights with more severe nocturnal hypoglycemia [5.5 (3.0) vs. 8.2 (2.3) mmol/L; p = 0.018 on nights with nadir sensor glucose of < 2.2 mmol/ L vs. 3.5 mmol/L]. There were only two instances of fasting capillary blood glucose >10 mmol/L after nocturnal hypoglycemia, both after likely treatment of the episode. When fasting capillary blood glucose is < 5 mmol/L, there was evidence of nocturnal hypoglycemia on 94% of nights. Conclusions Our data indicate that, in clinical practice, the Somogyi effect is rare. Fasting capillary blood glucose £ 5 mmol/L appears as an important indicator of preceding silent nocturnal hypoglycemia. Comment It is amazing that after all of these years we are still debating this topic. I continue to hear internal medicine residents teach this during patient rounds despite minimal evidence over the years that it exists. In fact, there was minimal evidence as noted 30 years ago (1)! However, the previous studies were all performed either retrospectively or with hypoglycemic clamps with bedside glucose testing. Using continuous glucose monitoring should (one would think) put an end to the misinformation about posthypoglycemic hyperglycemia. It will be interesting to listen to internal medicine residents 5 or 10 years from now about this phenomenon that doesn’t exist. Glucose variability assessed by low blood glucose index is predictive of hypoglycemic events in patients with type 1 diabetes switched to pump therapy Crenier L, Abou-Elias C, Corvilain B
SELF-MONITORING OF BLOOD GLUCOSE Department of Endocrinology, ULB-Erasme Hospital, Brussels, Belgium Diabetes Care 2013; 36: 2148–53
S-9 and Metabolism, Children’s Hospital Los Angeles, Los Angeles, CA; 4AMCR Institute, Escondido, CA; and 5Bayer HealthCare LLC, Diabetes Care, Tarrytown, NY Pediatr Diabetes 2013; 14: 350–57
Objective This study determined whether subgroups of type 1 diabetic patients with different glucose variability indices responded differently to continuous subcutaneous insulin infusion (CSII) in terms of reduced hypoglycemic events.
Aim The study assessed the performance and acceptability of a blood glucose meter coupled with a gaming system for children, adolescents, and young adults with type 1 diabetes.
Research and Methods
Methods
Fifty adults with long-standing type 1 diabetes switched to CSII because of persistently high A1C or frequent hypoglycemia despite well-managed intensive basal-bolus therapy. A1C, hypoglycemic events, and glucose variability from selfmonitoring of blood glucose profiles were compared at baseline and after 6 months of CSII. Regression analysis was performed to identify predictors of response.
During an in-clinic visit, duplicate blood samples were tested by subjects (N = 147; aged 5–24 years) and healthcare providers (HCPs) to evaluate the accuracy and precision of the Didget system. Subjects’ meter results were compared against Yellow Springs Instruments (YSI) reference results and HCP results using least squares regression and error grid analyses. Precision was measured by average within-subject and within-HCP coefficient of variation (CV). During the home-use component of this study, subjects (n = 58) tested their blood glucose at least two to three times daily for 3–5 days to evaluate routine use of the system.
Results In multivariate analysis, baseline low blood glucose index (LBGI) was the best independent predictor of hypoglycemia outcome on CSII (R(2) = 0.195, p = 0.0013). An ROC curve analysis demonstrated a sensitivity of 70.8% (95% CI: 48.9– 87.4) and specificity of 73.1% (52.2–88.4) by using the LBGI cutoff of 3.34 as predictor of reduction of hypoglycemia on CSII. By grouping patients by LBGI tertiles, we found a 23.3% reduction in hypoglycemic events (< 60 mg/dL [3.3 mmol/L]) in the third tertile (range 4.18–9.34) without change in A1C ( p < 0.05). Conversely, the first tertile (range 0.62–2.05) demonstrated the greatest A1C reduction, - 0.99% ( p = 0.00001), but with increasing hypoglycemia. Conclusions Baseline LBGI predicted the outcome of type 1 diabetic patients who switched to CSII in terms of hypoglycemia. Comment We were introduced to LGBI and its ability to predict severe hypoglycemia in 1998 (2). What makes this metric so valuable is that it is based on home blood glucose monitoring results. This is yet another study showing effectiveness of LBGI in type 1 diabetes, making one wonder why both clinicians and patients can’t have this available with routine glucose meter downloads. Evaluation of a combined blood glucose monitoring and gaming system (Didget) for motivation in children, adolescents, and young adults with type 1 diabetes Klingensmith GJ1, Aisenberg J 2, Kaufman F 3, Halvorson M 3, Cruz E1, Riordan ME 2, Varma C 4, Pardo S 5, Viggiani MT 5, Wallace JF 5, Schachner HC 5, Bailey T 4 1
Department of Pediatrics, Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, CO; 2Hackensack University Medical Center, Hackensack, NJ; 3Center for Diabetes, Endocrinology
Results Subjects’ meter results showed significant correlations with both YSI (r(2) = 0.94; p < 0.001 for regression slope) and HCP results (r(2) = 0.96; p < 0.001). Average within-subject and within-HCP CVs were 5.9% and 7.2%, respectively. Overall satisfaction was assessed by subjects, their parents or guardians, and HCP surveys. Subject satisfaction with the Didget system was good to excellent; most subjects found the system easy to use, motivating, and helpful for building good blood glucose monitoring habits. Most HCPs agreed that the system fulfilled a need in diabetes management. Conclusion The Didget system was precise and clinically accurate in the hands of children, adolescents, and young adults with type 1 diabetes. Comment Anything that improves motivation for SMBG would be welcomed, and it is reassuring that accuracy is acceptable with this system. The real question is how this system improves overall control on a long-term basis. Too many times a new ‘‘gizmo’’ is provided to try to improve outcomes, and more often than not this does not result in long-term behavior changes. A long-term study with Didget would be welcomed. Do currently available blood glucose monitors meet regulatory standards? One-day public meeting in Arlington, Virginia Klonoff DC1, Reyes JS 2 1
Mills Peninsula Health Services, San Mateo, CA; and Diabetes Technology Society, Foster City, CA
2
J Diabetes Sci Technol 2013; 7: 1071–83
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GARG AND HIRSCH
Blood glucose monitors (BGMs) are approved by regulatory agencies based on their performance during strict testing conducted by their manufacturers. However, after approval, there is uncertainty whether BGMs maintain the accuracy levels that were achieved in the initial data. The availability of inaccurate BGM systems pose a public health problem because their readings serve as a basis for treatment decisions that can be incorrect. Several articles have concluded that BGMs in the marketplace may not consistently provide accurate results in accordance with the regulatory standards that led to approval. To address this growing concern, Diabetes Technology Society organized and conducted a 1-day public meeting on May 21, 2013, in Arlington, VA, presided by its president, David Klonoff, MD, FACP, Fellow AIMBE, to determine whether BGMs on the market meet regulatory standards. The meeting consisted of four sessions in which Food and Drug Administration diabetes experts as well as leading academic clinicians and clinical chemists participated: (1) How is BGM performance determined? (2) Do approved BGMs perform according to International Organization for Standardization standards? (3) How do approved BGMs perform when used by patients and healthcare professionals? (4) What could be the consequence of poor BGM performance?
modeling analysis on the impact on hypoglycemic episodes, glycosylated hemoglobin (HbA1c), and, subsequently, myocardial infarctions; and (4) costs of diabetes-related complications in Germany. A reduction of meter error from 20% to 5% was identified to be associated with a 10% reduction in severe hypoglycemic episodes and a 0.39% reduction in HbA1c, which translates into a 0.5% reduction of myocardial infarctions.
Comment Moving forward, the topic of blood glucose strip accuracy is one of the most important concerns in the field. In the United States, the introduction of ‘‘competitive bidding’’ from nontraditional (or ‘‘off-brand’’) glucose test manufacturers has resulted in studies showing unacceptable accuracy. The regulatory ‘‘loopholes’’ of how these strips get onto the market and then stay on the market are a major concern for both providers and patients alike. Hopefully, these issues will be resolved in the near future.
Comment A ‘‘modeling analysis’’ is full of potential errors from assumptions that are potentially not valid. Nevertheless, this study suggests surprising and substantial cost savings with improvements of blood glucose meter accuracy. Perhaps more importantly, improvements in overall quality of health need to be appreciated. A true randomized trial comparing different meters with different accuracies is unlikely to be performed.
Results According to the health economic analysis, the reduction in severe hypoglycemic episodes and myocardial infarctions led to cost savings of e24.14 per patient per year. Considering 390,000 type 1 diabetes patients or 2.3 million insulin-treated patients in Germany, these savings could be equal to a reduction in healthcare expenditures of more than e9.4 million and e55.5 million, respectively. Conclusion Potential cost savings and clinical effects due to higher accuracy of BG meters should provide an impetus to implement tighter accuracy standards and develop glucose meters that provide highest possible accuracy.
Higher accuracy of self-monitoring of blood glucose in insulin-treated patients in Germany: clinical and economical aspects
Evaluation of a blood glucose monitoring system with automatic high- and low-pattern recognition software in insulin-using patients: pattern detection and patient-reported insights
Schnell O 1, Erbach M 2, Wintergerst E 3
Grady M 1, Campbell D 1, MacLeod K 1, Srinivasan A2
1
1
Forschergruppe Diabetes e.V., Helmholtz Center Munich, Munich-Neuherberg, Germany; 2Sciarc Institute, Baierbrunn, Germany; and 3Bayer Healthcare Diabetes Care, Basel, Switzerland
LifeScan Scotland Ltd., Inverness, UK; 2LifeScan, Inc., Milpitas, CA
J Diabetes Sci Technol 2013; 7: 970–78 Comment in: J Diabetes Sci Technol 2013; 7: 979–82
J Diabetes Sci Technol 2013; 7: 904–12
Background Background Accuracy standards of blood glucose (BG) meters are currently under review. Revised standards are expected to tighten accuracy requirements. Regarding clinical and financial impact of BG meter accuracy, very little data are available. This study analyzed the potential cost savings related to higher accuracy of glucose meters in Germany. Methods As a model for calculation, a reduction of meter error from 20% to 5% was applied. The health economic analysis was based on four main pillars: (1) number of insulin-treated patients; (2) costs for glucose monitoring in Germany; (3) data of a
This study aimed to evaluate the performance of a glucose pattern recognition tool incorporated in a blood glucose monitoring system (BGMS) and its association with clinical measures, and to assess user perception and understanding of the pattern messages they receive. Methods Participants had type 1 or type 2 diabetes mellitus and were self-adjusting insulin doses for ‡1 year. During a 4-week home testing period, participants performed ‡ 6 daily selftests, adjusted their insulin regimen based on BGMS results, and recorded pattern messages in the logbook. Participants reflected on usability of the pattern tool in a questionnaire.
SELF-MONITORING OF BLOOD GLUCOSE
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Results
Conclusions
Study participants (N = 101) received a mean – standard deviation of 4.5 – 1.9 pattern messages per week (3.6 – 1.8 high glucose patterns and 0.9 – 1.3 low glucose patterns). Most received ‡ 1 high (96.5%) and/or ‡ 1 low (46.0%) pattern message per week. The average number of high- and low-pattern messages per week was associated with higher and lower, respectively, baseline hemoglobin A1c ( p < 0.01) and fasting plasma glucose ( p < 0.05). Participants found high- and low-pattern messages clear and easy to understand (84.2% and 83.2%, respectively) and considered the frequency of low (82.0%) and high (63.4%) pattern messages about right. Overall, 71.3% of participants preferred to use a meter with pattern messages.
SMBG continues to be an integral part of day-to-day management for people with type 1 diabetes and insulinrequiring patients with type 2 diabetes. Since CGMs are only approved as adjunctive, the role of SMBG in calibrating CGMs and cross-checking the glucose values with SMBG before acting on CGM values is indicated. Fortunately, the cost of SMBG strips is coming down, and we hope that it does not jeopardize further development of better technology for accurate SMBG strips. It is important to keep in mind that SMBG results in better health outcomes (improved A1c values) only if patients are advised on what to do with the SMBG values, and thus the role of education in the use of SMBG data is most important.
Conclusion The on-device Pattern tool identified meaningful blood glucose patterns, highlighting potential opportunities for improving glycemic control in patients who self-adjust their insulin.
Author Disclosure Statement No competing financial interests exist.
Comment As we are well into the era of ‘‘smart phones,’’ ‘‘smart watches,’’ and even ‘‘smart insulin pumps,’’ it seems that we certainly should have better technology for helping patients with real-time pattern recognition. Pattern messaging from glucose meters (or CGM devices) should be the standard of care, especially if studies continue to show good acceptance, improvements of A1C, and reductions of hypoglycemia.
References 1. Raskin P. The Somogyi phenomenon: sacred cow or bull? Arch Intern Med 1984; 144: 784–87. 2. Kovatchev BP, Cox DJ, Gonder-Frederick LA, et al. Assessment of risk for severe hypoglycemia among adults with IDDM: Validation of the low blood glucose index. Diabetes Care 1998; 21: 1870–75.
ORIGINAL ARTICLE
Self-Monitoring of Blood Glucose Satish K. Garg1 and Irl B. Hirsch 2
Introduction
T
he role of self-monitoring of blood glucose (SMBG) in diabetes management continues to be debated especially for type 2 diabetes (T2D). Since continuous glucose monitoring (CGM) is only approved as adjunctive to SMBG, its role in self-management of type 1 diabetes (T1D) is at least noncontroversial. Most of the literature supports use of frequent SMBG in T1D for better glucose control. The controversy for SMBG use in T2D is partly due to continued advertisements of ‘‘no need of monitoring’’ by the industry that makes noninsulin products. It is true that if SMBG information is not used to adjust insulin dose or medication dose adjustments (that can be made every 3 months based on A1c values), the exact role of SMBG in T2D remains controversial. The other side of the coin is to detect glycemic patterns and hypoglycemia that may require early attention/therapeutic changes for better diabetes care in the early course of T2D rather than having to wait for a change in A1c values, which may take several months/years. The cost of meter strips has come down significantly to *$10.00 for a box of 50 strips at least in the United States as per ‘‘government mandate.’’ Emergence of generic strips and the reduction in the cost may have impacted the future development of more accurate meters/strips especially as mandated by the FDA (new ISO standards) that all meters must meet within 15% of the standard glucose values as highlighted in the 2013 yearbook. We discuss in this article the role of SMBG in T1D, T2D, and inpatients. The future may rely on the use and application of SMBG data for mobile applications to improve real-life diabetes outcomes.
and support. Blood glucose monitoring and patient education are essential in diabetes care and management, and if used appropriately, can help to achieve maximum benefit for the patient and diabetes care team. The link between blood glucose levels and the incidence of diabetes-related complications are considered in this study. The different blood glucose monitoring strategies, particularly self-monitoring of blood glucose in people with type 2 diabetes, are evaluated. The frequency of blood glucose monitoring and the identification of patterns and trends in blood glucose control are highlighted and applied to practice. Comment This article highlights the need and the value of SMBG in type 2 diabetes. More importantly, the article brings out its role for long-term complications of type 2 diabetes if glucose patterns are evaluated and necessary action is taken for therapeutic changes in time. A glucose meter evaluation co-designed with both health professional and consumer input Thompson H 1, Chan H 2, Logan FJ 2, Heenan HF 2, Taylor L 2, Murray C 2, Florkowski CM 3, Frampton CM 4, Lunt H 2 University of Otago, Christchurch, New Zealand; 2Diabetes Centre, Christchurch, New Zealand; 3Canterbury Health Laboratories, Christchurch, New Zealand; and 4 Department of Medicine, University of Otago, Christchurch, New Zealand
1
N Z Med J 2013; 126: 90–97
Blood glucose monitoring in diabetes Holt P
Introduction
School of Healthcare, University of Leeds, UK Nurs Stand 2014; 28: 52–58
Diabetes is one of the few chronic conditions that individuals can successfully manage and control on a day-to-day basis, providing that they have access to appropriate advice
Health consumers’ input into assessment of medical device safety is traditionally given either as part of study outcome (trial participants) or during post-marketing surveillance. Direct consumer input into the methodological design of device assessment is less common.
1
University of Colorado Health Sciences Center, Aurora, CO. University of Washington Medical Center, Seattle, WA.
2
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S-4 Methods In this study, the difference in requirements for assessment of a measuring device from the consumer and clinician perspectives, using the example of hand-held glucose meters, are reviewed. Around 80,000 New Zealanders with diabetes recently changed their glucose meter system to enable ongoing access to PHARMAC-subsidized meters and strips. Consumers were more interested in a direct comparison of their ‘‘old’’ meter system (Accu-Chek Performa) with their ‘‘new’’ meter system (CareSens brand, including the CareSens N POP), rather than comparisons against a laboratory standard.
GARG AND HIRSCH dynamic electrochemistry to correct for potential interferences and thereby minimize system errors. Research and Methods A single-center, in vitro diagnostic device performance evaluation with heparinized oxygenated venous blood samples (intra-assay precision) and control solutions (interassay precision) was performed in a laboratory setting, comparing BGStar and iBGStar with 12 competitors. The primary outcome was the coefficient of variation percent (CV%) of the BGMs investigated.
Results
Results
This direct comparison of meter/strip systems showed that the CareSens N POP meter read approximately 0.6 mmol/L higher than the Performa system.
In interassay precision analyses, all but GlucoMen LX had a CV < 5%, and in intra-assay precision analyses, 10 of the 14 devices tested had CV < 5%. BGStar and iBGStar had a CV < 5% in both the inter- and intra-assay precision analyses. The smallest variation was found in the near-normoglycemic glucose range (5.3–8.0 mmol/L) for both BGStar and iBGStar in the interassay precision analysis.
Conclusion While this difference is unlikely to result in major errors in clinical decision making such as major insulin dosing errors, this information is nevertheless of interest to consumers who switched meters so that they could maintain access to PHARMAC-subsidized meters and strips. We recommend that when practical, the consumer perspective be incorporated into study design related to medical device assessment. Comment This is an important study that evaluates patient’s response to a generic meter and strips in an attempt to reduce the cost to the health-care system in New Zealand. Even though the new meter/strips were reading glucose readings by about 10 mg/dL higher than the standard Accu-Chek meter, this difference is unlikely to impact ongoing diabetes care by the patients. I agree with the authors’ conclusions that going forward patients’ perspectives may need to be evaluated while determining efficacy of the new meters/strips system rather than doing the traditional study of comparing with Yellow Springs Instruments or the auto-analyzer. The precision study: examining the interand intra-assay variability of replicate measurements of BGStar, iBGStar, and 12 other blood glucose monitors
Conclusions BGStar and iBGStar were proven to have very good interassay and high intra-assay precision, demonstrating low scattering of replicate measurements with both clinical samples and control solutions. Comment Here is an example of an industry-sponsored study showing that the iBGStar had the lowest CV in both inter- and intra-assay precision analysis. Such studies should ideally be done without any industry bias and in an academic setting, since we are likely to see many new meter/strip systems designed for patient use in a more cost-effective way. Fasting glucose level is associated with nocturnal hypoglycemia in elderly male patients with type 2 diabetes Fang F, Xiao H, Li C, Tian H, Li J, Li Z, Cheng X Department of Geriatric Endocrinology, Chinese PLA General Hospital, Beijing, PR China
Ramljak S1, Musholt PB 1, Schipper C 1, Flacke F 2, Sieber J 2, Borchert M 3, Forst T1, Pfu¨tzner A 1
Aging Male 2013; 16: 132–36
1
Background
Expert Opin Med Diagn 2013; 7: 511–16
Nocturnal hypoglycemia is a common and serious problem among patients with type 2 diabetes (T2DM), especially in the elderly. This study investigated whether fasting glucose is an indicator of nocturnal hypoglycemia in elderly male patients with T2DM.
IKFE–Institute for Clinical Research and Development, Mainz, Germany; and 2Sanofi, Frankfurt, Germany; 3IKFE CRO, Mainz, Germany
Objective Self-monitoring of blood glucose is a key element in diabetes management. Accurate and precise performance of blood glucose monitors (BGMs) ensures that valid values are obtained to guide treatment decisions by patients and physicians. BGStar and iBGStar are hand-held BGMs that use
Methods A total of 291 elderly male patients with type 2 diabetes who received continuous glucose monitoring (CGM) between January 2007 and January 2011 were enrolled in the
SELF-MONITORING OF BLOOD GLUCOSE study. The association of fasting glucose and nocturnal hypoglycemia based on CGM data was analyzed, comparing with bedtime glucose. Results Based on CGM data, patients with nocturnal hypoglycemia had significantly lower fasting glucose (5.88 – 1.29 vs. 6.92 – 1.32 mmol/L) and bedtime glucose (7.33 – 1.70 vs. 8.01 – 1.95 mmol/L) than patients without nocturnal hypoglycemia (both p < 0.01). Compared with the highest quartile, the lowest quartile of fasting glucose had a significantly increased risk of nocturnal hypoglycemia after the multiple adjustments ( p for trend < 0.001). However, this association did not appear in bedtime glucose. When predicting nocturnal hypoglycemia either by fasting glucose or bedtime glucose using the area under receiver operating characteristic (ROC) curve, fasting glucose, but not bedtime glucose, was an indicator of nocturnal hypoglycemia, with an area under the ROC curve (AUC) of 0.714 (95% CI: 0.653–0.774, p < 0.001). On the ROC curve, the Youden index was maximal when fasting glucose was 6.1 mmol/L.
S-5 Italy; 5Department of Internal Medicine, University of Turin, Turin, Italy; 6Division of Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Padova, Padua, Italy; 7Diabetes Unit, Ospedale Madonna del Soccorso, S. Benedetto del Tronto, Italy; 8Medical Department Roche S.p.A, Monza, Italy; 9Medical Affairs Department Roche Diagnostics S.p.A., Monza, Italy; 10Information and Education Development, CGParkin, Inc., Las Vegas, NV; 11Section of Medical Statistics and Biometry GA Maccacaro, Department of Occupational Health Clinica del Lavoro L Devoto, School of Medicine, University of Milan, Milan, Italy; and 12Department of Internal Medicine, Policlinico Universitario Gaetano Martino, Messina, Italy Acta Diabetol 2013; 50: 663–72
Introduction Self-monitoring of blood glucose (SMBG) is a core component of diabetes management. However, the International Diabetes Federation recommends that SMBG be performed in a structured manner and that the data are accurately interpreted and used to take appropriate therapeutic actions.
Conclusion
Design and Methods
Fasting glucose may be a convenient and clinically useful indicator of nocturnal hypoglycemia in elderly male patients with T2DM. Risk of nocturnal hypoglycemia significantly increased when fasting glucose was less than 6.1 mmol/L.
We designed a study to evaluate the impact of structured SMBG on glycemic control in non-insulin-treated type 2 diabetes (T2DM) patients. The Prospective, Randomized Trial on Intensive SMBG Management Added Value in Non-InsulinTreated T2DM Patients (PRISMA) is a 12-month, prospective, multicenter, open, parallel-group, randomized, and controlled trial to evaluate the added value of an intensive, structured SMBG regimen in T2DM patients treated with oral agents and/ or diet. One thousand patients (500 per arm) will be enrolled at 39 clinical sites in Italy. Eligible patients will be randomized to the intensive structured monitoring (ISM) group or the active control (AC) group, with a glycosylated hemoglobin (HbA1c) target of < 7.0%. Intervention will comprise (a) structured SMBG (4-point daily glucose profiles on 3 days per week [ISM]; discretionary, unstructured SMBG [AC]); (b) comprehensive patient education (both groups); and (c) clinician’s adjustment of diabetes medications using an algorithm targeting SMBG levels, HbA1c and hypoglycemia (ISM) or HbA1c and hypoglycemia (AC).
Comment Severe hypoglycemia is an important problem in the elderly on insulin therapy with type 1 and type 2 diabetes, especially because of hypoglycemic unawareness and altered cognitive abilities due to long-term duration of diabetes. This continues to be the leading cause of increased hospital admissions in the United States. Thus, the new technology use in this population might prevent unnecessary hospitalizations, reduce healthcare costs, and improve overall quality of life. The above study highlights the role of CGM, especially the glucose values (less than 6.1 mmol/L), in the fasting state that determine the high risk of nocturnal hypoglycemia. Prospective, randomized trial on intensive SMBG management added value in non-insulin-treated T2DM patients (PRISMA): a study to determine the effect of a structured SMBG intervention Scavini M 1, Bosi E 1,2, Ceriello A 3, Giorgino F 4, Porta M 5, Tiengo A 6, Vespasiani G 7, Bottalico D 8, Marino R 9, Parkin C 10, Bonizzoni E 11, Cucinotta D 12 1
Diabetes Research Institute, San Raffaele Scientific Institute, Milan, Italy; 2San Raffaele Vita-Salute University, Milan, Italy; 3Institut d’Investigacions Biome`diques August Pi Sunyer (IDIBAPS) and Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadis (CIBERDEM), Barcelona, Spain; 4Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari School of Medicine, Bari,
Conclusion The intervention and trial design will build upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of perprotocol and intent-to-treat analyses facilitates assessment of the intervention. Inclusion of multiple dependent variables allows a broader impact assessment of the intervention, including changes in patient and physician attitudes and behaviors. Intensive structured self-monitoring of blood glucose and glycemic control in non-insulintreated type 2 diabetes: the PRISMA randomized trial Bosi E 1,2, Scavini M 1,2, Ceriello A 3, Cucinotta D 4, Tiengo A 5, Marino R 6, Bonizzoni E 7, Giorgino F 8; PRISMA Study Group
S-6 1
Diabetes Research Institute, San Raffaele Hospital and Scientific Institute, Milan, Italy; 2San Raffaele Vita-Salute University, Milan, Italy; 3Institut d’Investigacions Biome`diques August Pi Sunyer and Centro de Investigacion Biomedica en Red de Diabetes y Enfermedades Metabolicas Asociadis, Barcelona, Spain; 4Department of Internal Medicine, Policlinico Universitario Gaetano Martino, Messina, Italy; 5Division of Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Padova, Padova, Italy; 6Medical Affairs, Roche Diagnostics, Monza, Italy; 7 Section of Medical Statistics and Biometry G.A. Maccacaro, Department of Occupational Health Clinica del Lavoro L. Devoto, School of Medicine, University of Milan, Milan, Italy; and 8Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari School of Medicine, Bari, Italy Diabetes Care 2013; 36: 2887–94 Comment in: Diabetes Care 2013; 36: e217; Diabetes Care 2013; 36: e218
Objective
GARG AND HIRSCH Self-monitoring of blood glucose in type 2 diabetes: patients’ perceptions of ‘‘high’’ readings Evans JM1, Mackison D 1, Swanson V 2, Donnan PT 3, Emslie-Smith A 4, Lawton J 5 1
School of Nursing, Midwifery and Health, University of Stirling, Scotland, UK; 2School of Natural Sciences, University of Stirling, Scotland, UK; 3Dundee Epidemiology and Biostatistics Unit, Division of Population Health Sciences, Medical Research Institute, University of Dundee, Scotland, UK; 4The Mill Practice, Dundee, Scotland, UK; and 5Centre for Population Health Sciences, University of Edinburgh, Scotland, UK
Diabetes Res Clin Pract 2013; 102: e5–7
Among 207 non-insulin-using patients with type 2 diabetes in Tayside, Scotland, who self-monitored blood glucose, we present evidence that many are tolerant of higher blood glucose levels than are clinically advisable. This may explain the lack of empirical evidence for the clinical benefits of selfmonitoring in this group. Comment The above four studies highlight the importance of SMBG in type 2 diabetes. The PRISMA study published earlier highlights the importance of structured SMBG monitoring for patients with type 2 diabetes. The other study highlights the patients’ perceptions of high readings. Patients are usually more tolerant of higher blood glucose values than advisable, and thus the exact role of SMBG in type 2 diabetes may be difficult to evaluate in real life.
The added value of intensive self-monitoring of blood glucose (SMBG), structured in timing and frequency, in noninsulin-treated patients with type 2 diabetes was evaluated. Research Design and Methods The 12-month, randomized, clinical trial enrolled 1,024 patients with non-insulin-treated type 2 diabetes (median baseline HbA1c, 7.3% [IQR, 6.9–7.8%]) at 39 diabetes clinics in Italy. After standardized education, 501 patients were randomized to intensive structured monitoring (ISM) with 4-point glycemic profiles (fasting, preprandial, 2 h postprandial, and postabsorptive measurements) performed 3 days/week; 523 patients were randomized to active control (AC) with 4-point glycemic profiles performed at baseline and at 6 and 12 months. Two primary end points were tested in hierarchical order: HbA1c change at 12 months and percentage of patients at risk target for low and high blood glucose index. Results Intent-to-treat analysis showed greater HbA1c reductions over 12 months in ISM ( - 0.39%) than in AC patients ( - 0.27%), with a between-group difference of - 0.12% (95% CI, - 0.210 to - 0.024; p = 0.013). In the per-protocol analysis, the betweengroup difference was - 0.21% ( - 0.331 to - 0.089; p = 0.0007). More ISM than AC patients achieved clinically meaningful reductions in HbA1c ( > 0.3%, > 0.4%, or > 0.5%) at study end ( p < 0.025). The proportion of patients reaching/maintaining the risk target at month 12 was similar in ISM (74.6%) and AC (70.1%) patients ( p = 0.131). At visits 2, 3, and 4, diabetes medications were changed more often in ISM than in AC patients ( p < 0.001). Conclusion Use of structured SMBG improves glycemic control and provides guidance in prescribing diabetes medications in patients with relatively well-controlled non-insulin-treated type 2 diabetes.
Determinants of self-monitoring of blood glucose in patients with type 1 diabetes: a multicenter study in Brazil Gomes MB1, Tannus LR 1, Cobas RA 1, Matheus AS 1, Dualib P 2,3, Zucatti AT 3, Cani C 4, Guedes AD 5, Santos FM 6, Sepulveda J 7, Tolentino M 8, Fac¸anha MC 9, Faria AC 10, Lavigne S11, Montenegro AP 12, Rodacki M 13, de Fatima Guedes M 14, Szundy R 13, Cordeiro MM15, Santos PT 16, Negrato CA 14; Brazilian Type 1 Diabetes Study Group (BrazDiab1SG) 1
Diabetes Unit, Department of Internal Medicine, State University Hospital of Rio de Janeiro, Sa˜o Paulo, Brazil; 2 Diabetes Unit, Federal University of Sa˜o Paulo State, Sa˜o Paulo, Brazil; 3Federal University Hospital of Porto Alegre, Rio Grande do Sul, Brazil; 4Diabetes Unit, University Hospital of Sa˜o Paulo, Sa˜o Paulo, Brazil; 5Centro de Diabetes do Estado da Bahia, Para´, Brazil; 6Federal University Hospital Joa˜o Barreto, Para´, Brazil; 7Endocrinology Unit, Santa Casa Hospital of Belo Horizonte, Minas Gerais, Brazil; 8Taguatinga Regional Hospital, Brası´lia, Brazil; 9 Diabetes and Hypertension Research Center, Federal University of Ceara´, Ceara´, Brazil; 10Federal University Hospital of Parana´, Parana´, Brazil; 11Instituto da Crianc¸a com Diabete Rio Grande Sul, Ceara´, Brazil; 12Federal University of Ceara´, Ceara´, Brazil; 13Federal University Hospital of Rio de Janeiro, Rio de Janeiro, Brazil;
SELF-MONITORING OF BLOOD GLUCOSE 14
Bauru’s Diabetics Association, Department of Internal Medicine, Bauru, Sa˜o Paulo, Brazil; 15General Hospital of Bonsucesso, Rio de Janeiro, Brazil; and 16Genetic Department National Institute of Cancer, Hospital of Bonsucesso, Bonsucesso, Brazil Diabetic Med 2013; 30: 1255–62
S-7 Objective To determine whether personality traits (conscientiousness, agreeableness, emotional regulation, extraversion, and openness to experience) are associated with glycemic control and blood glucose monitoring behavior, and change or stability of these outcomes over time, in young people with type 1 diabetes.
Aim This study determined the relationship between the daily frequency of self-monitoring of blood glucose and glycemic control, and demographic and socioeconomic status in patients with type 1 diabetes under routine clinical care in Brazil. Methods A cross-sectional, multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,176 patients, aged 22 – 11.8 years, of whom 56.3% were female and 57.4% were Caucasian. The mean time since diabetes diagnosis was 11.7 – 8.1 years. Results The prevalence of self-monitoring of blood glucose was 88.5%. There was a significant increase in self-monitoring frequency associated with female gender, lower ages, more intensive diabetes management, and higher socioeconomic status. A correlation between HbA1c levels and the daily frequency of self-monitoring was observed [r(s) = - 0.13; p = 0.001]. The mean HbA1c levels were related to the daily frequency of self-monitoring ( p < 0.001) without additional benefit to patients who performed self-monitoring more than four times daily (9.2%, 11.2%, 10.2%, 15.2%, and 15% for one, two, three, four, five, or more self-monitoring tests daily, respectively; p < 0.0001). Conclusion The majority of our patients (88.5%) performed three or more self-monitoring tests daily, with more frequent testing reported by females, younger patients, and those on intensive insulin regimens and of higher socioeconomic status. No additional benefit was found in patients who performed selfmonitoring more than four times daily. The diabetes care team must improve patients’ education regarding selfmonitoring of blood glucose and its benefits. Glycemic control and blood glucose monitoring over time in a sample of young Australians with type 1 diabetes: the role of personality Waller D 1, Johnston C 1, Molyneaux L 2, Brown-Singh L1, Hatherly K 3, Smith L 3, Overland J 2,4 1
School of Education, University of Western Sydney, Penrith, New South Wales, Australia; 2Diabetes Centre, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia; and 3Faculty of Pharmacy and 4Sydney School of Nursing, University of Sydney, Sydney, New South Wales, Australia
Diabetes Care 2013; 36: 2968–73
Methods A 3-year longitudinal study was conducted using data from 142 individuals with type 1 diabetes, 8–19 years of age. Personality was assessed at baseline using the Five-Factor Personality Inventory for Children. Data relating to glycemic control (HbA1c) and frequency of blood glucose monitoring (based on meter memory) were collected annually. Relationships between personality traits and HbA1c and monitoring frequency were examined using regression analysis and mixed-design ANOVA. Results Three of the Five-Factor domains were independently associated with glycemic control. Individuals high in conscientiousness and agreeableness had a lower and more stable HbA1c across the 3-year study period. In contrast, the HbA1c of individuals scoring low on these traits was either consistently worse or deteriorated over time. Low or high emotional regulation scores were also associated with worse glycemic control. By the third year, these domains, together with initial HbA1c, accounted for 39% of HbA1c variance. Conscientiousness was the only personality factor associated with blood glucose monitoring behavior. Conclusion Results of this study underline the importance of personality in contributing to diabetes outcomes. Attention to a young person’s personality, and appropriate tailoring of diabetes management to ensure an individualized approach, may help to optimize diabetes outcomes. Comment The above two studies document the importance of personality and the role of frequent glucose monitoring in type 1 diabetes. The type 1 Diabetes Exchange data from the United States that include more than 25,000 patients from 70 leading centers in the United States concluded that frequent glucose monitoring (SMBG) was associated with lowered A1c values in a crosssectional real-life study. The drop in A1c was proportional to the frequency of glucose monitoring. On the contrary, the above study from Brazil found no additional benefit from SMBG if performed more than four times a day. This was also a real-life study; however, the sample size was much smaller as compared to the type 1 Diabetes Exchange data. The authors do conclude that better education is needed for improving outcomes in patients with type 1 diabetes.
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GARG AND HIRSCH
SMBG out of control: the need for educating patients about control solution
Aims
This project was conducted to determine how prevalent control solution calibration is in patients who perform selfmonitoring of blood glucose (SMBG).
The Somogyi effect postulates that nocturnal hypoglycemia causes fasting hyperglycemia attributable to counterregulatory hormone release (although most published evidence failed to support this hypothesis). This concept remains firmly embedded in clinical practice and often prevents patients and professionals from optimizing overnight insulin. Previous observational data found that lower fasting glucose was associated with nocturnal hypoglycemia, but did not assess the probability of infrequent individual episodes of rebound hypoglycemia. Continuous glucose monitoring data were analyzed to explore its prevalence.
Methods
Methods
Eighteen patients with or parents of children with type 1 diabetes mellitus were surveyed to gauge patients’ knowledge of control testing and the prevalence of its use. U.S. census data on educational attainment of residents in the surveyed region were used. The availability of control solution (CS) in all pharmacies in eight cities in mid–San Mateo County, California, was evaluated as well. User manuals from six leading blood glucose monitor (BGM) manufacturers were retrieved for their indications for using CS.
Data from 89 patients with type 1 diabetes who participated in the UK hypoglycemia study were analyzed. Fasting capillary glucose following nights with and without nocturnal hypoglycemia (sensor glucose < 3.5 mmol/L) were compared.
Chaudhry T, Klonoff DC Diabetes Research Institute, Services, San Mateo, CA
Mills-Peninsula
Health
Diabetes Educ 2013; 39: 689–95
Purpose
Results It was found that although 82% of respondents claimed to know what CS is, 58% claimed to never use this product. In the geographic region analyzed, the educational attainment was above the educational level for the entire San Francisco Bay Area and the United States. CS in our region was stocked by only 15% of pharmacies that sold BGM equipment, even though 6 major BGM manufacturers in the aggregate listed 10 indications for its use. Conclusions BGM users are frequently not using CS to calibrate their monitors. The low availability of CS at pharmacies might contribute to the low demand for this product. Patients who perform SMBG need education from diabetes educators about proper CS calibration. Without the use of CS, BGMs are not being used according to manufacturer’s specifications. This misuse could lead to erroneous results and erode the potential benefits of SMBG. Comment This has been a topic that has had minimal visibility, compared to the industry’s ability to provide ‘‘no-code’’ strips. One has to wonder how accuracy would improve if CS was more uniformly used as instructed by the manufacturers. Do high fasting glucose levels suggest nocturnal hypoglycemia? The Somogyi effect—more fiction than fact? Choudhary P, Davies C, Emery CJ, Heller SR Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, UK Diabetic Med 2013; 30: 914–17 Comment in: Diabetic Med 2013; 30: 889–90
Results Fasting capillary blood glucose was lower after nights with hypoglycemia than without [5.5 (3.0) vs. 14.5 (4.5) mmol/L, p < 0.0001], and was lower on nights with more severe nocturnal hypoglycemia [5.5 (3.0) vs. 8.2 (2.3) mmol/L; p = 0.018 on nights with nadir sensor glucose of < 2.2 mmol/ L vs. 3.5 mmol/L]. There were only two instances of fasting capillary blood glucose >10 mmol/L after nocturnal hypoglycemia, both after likely treatment of the episode. When fasting capillary blood glucose is < 5 mmol/L, there was evidence of nocturnal hypoglycemia on 94% of nights. Conclusions Our data indicate that, in clinical practice, the Somogyi effect is rare. Fasting capillary blood glucose £ 5 mmol/L appears as an important indicator of preceding silent nocturnal hypoglycemia. Comment It is amazing that after all of these years we are still debating this topic. I continue to hear internal medicine residents teach this during patient rounds despite minimal evidence over the years that it exists. In fact, there was minimal evidence as noted 30 years ago (1)! However, the previous studies were all performed either retrospectively or with hypoglycemic clamps with bedside glucose testing. Using continuous glucose monitoring should (one would think) put an end to the misinformation about posthypoglycemic hyperglycemia. It will be interesting to listen to internal medicine residents 5 or 10 years from now about this phenomenon that doesn’t exist. Glucose variability assessed by low blood glucose index is predictive of hypoglycemic events in patients with type 1 diabetes switched to pump therapy Crenier L, Abou-Elias C, Corvilain B
SELF-MONITORING OF BLOOD GLUCOSE Department of Endocrinology, ULB-Erasme Hospital, Brussels, Belgium Diabetes Care 2013; 36: 2148–53
S-9 and Metabolism, Children’s Hospital Los Angeles, Los Angeles, CA; 4AMCR Institute, Escondido, CA; and 5Bayer HealthCare LLC, Diabetes Care, Tarrytown, NY Pediatr Diabetes 2013; 14: 350–57
Objective This study determined whether subgroups of type 1 diabetic patients with different glucose variability indices responded differently to continuous subcutaneous insulin infusion (CSII) in terms of reduced hypoglycemic events.
Aim The study assessed the performance and acceptability of a blood glucose meter coupled with a gaming system for children, adolescents, and young adults with type 1 diabetes.
Research and Methods
Methods
Fifty adults with long-standing type 1 diabetes switched to CSII because of persistently high A1C or frequent hypoglycemia despite well-managed intensive basal-bolus therapy. A1C, hypoglycemic events, and glucose variability from selfmonitoring of blood glucose profiles were compared at baseline and after 6 months of CSII. Regression analysis was performed to identify predictors of response.
During an in-clinic visit, duplicate blood samples were tested by subjects (N = 147; aged 5–24 years) and healthcare providers (HCPs) to evaluate the accuracy and precision of the Didget system. Subjects’ meter results were compared against Yellow Springs Instruments (YSI) reference results and HCP results using least squares regression and error grid analyses. Precision was measured by average within-subject and within-HCP coefficient of variation (CV). During the home-use component of this study, subjects (n = 58) tested their blood glucose at least two to three times daily for 3–5 days to evaluate routine use of the system.
Results In multivariate analysis, baseline low blood glucose index (LBGI) was the best independent predictor of hypoglycemia outcome on CSII (R(2) = 0.195, p = 0.0013). An ROC curve analysis demonstrated a sensitivity of 70.8% (95% CI: 48.9– 87.4) and specificity of 73.1% (52.2–88.4) by using the LBGI cutoff of 3.34 as predictor of reduction of hypoglycemia on CSII. By grouping patients by LBGI tertiles, we found a 23.3% reduction in hypoglycemic events (< 60 mg/dL [3.3 mmol/L]) in the third tertile (range 4.18–9.34) without change in A1C ( p < 0.05). Conversely, the first tertile (range 0.62–2.05) demonstrated the greatest A1C reduction, - 0.99% ( p = 0.00001), but with increasing hypoglycemia. Conclusions Baseline LBGI predicted the outcome of type 1 diabetic patients who switched to CSII in terms of hypoglycemia. Comment We were introduced to LGBI and its ability to predict severe hypoglycemia in 1998 (2). What makes this metric so valuable is that it is based on home blood glucose monitoring results. This is yet another study showing effectiveness of LBGI in type 1 diabetes, making one wonder why both clinicians and patients can’t have this available with routine glucose meter downloads. Evaluation of a combined blood glucose monitoring and gaming system (Didget) for motivation in children, adolescents, and young adults with type 1 diabetes Klingensmith GJ1, Aisenberg J 2, Kaufman F 3, Halvorson M 3, Cruz E1, Riordan ME 2, Varma C 4, Pardo S 5, Viggiani MT 5, Wallace JF 5, Schachner HC 5, Bailey T 4 1
Department of Pediatrics, Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, CO; 2Hackensack University Medical Center, Hackensack, NJ; 3Center for Diabetes, Endocrinology
Results Subjects’ meter results showed significant correlations with both YSI (r(2) = 0.94; p < 0.001 for regression slope) and HCP results (r(2) = 0.96; p < 0.001). Average within-subject and within-HCP CVs were 5.9% and 7.2%, respectively. Overall satisfaction was assessed by subjects, their parents or guardians, and HCP surveys. Subject satisfaction with the Didget system was good to excellent; most subjects found the system easy to use, motivating, and helpful for building good blood glucose monitoring habits. Most HCPs agreed that the system fulfilled a need in diabetes management. Conclusion The Didget system was precise and clinically accurate in the hands of children, adolescents, and young adults with type 1 diabetes. Comment Anything that improves motivation for SMBG would be welcomed, and it is reassuring that accuracy is acceptable with this system. The real question is how this system improves overall control on a long-term basis. Too many times a new ‘‘gizmo’’ is provided to try to improve outcomes, and more often than not this does not result in long-term behavior changes. A long-term study with Didget would be welcomed. Do currently available blood glucose monitors meet regulatory standards? One-day public meeting in Arlington, Virginia Klonoff DC1, Reyes JS 2 1
Mills Peninsula Health Services, San Mateo, CA; and Diabetes Technology Society, Foster City, CA
2
J Diabetes Sci Technol 2013; 7: 1071–83
S-10
GARG AND HIRSCH
Blood glucose monitors (BGMs) are approved by regulatory agencies based on their performance during strict testing conducted by their manufacturers. However, after approval, there is uncertainty whether BGMs maintain the accuracy levels that were achieved in the initial data. The availability of inaccurate BGM systems pose a public health problem because their readings serve as a basis for treatment decisions that can be incorrect. Several articles have concluded that BGMs in the marketplace may not consistently provide accurate results in accordance with the regulatory standards that led to approval. To address this growing concern, Diabetes Technology Society organized and conducted a 1-day public meeting on May 21, 2013, in Arlington, VA, presided by its president, David Klonoff, MD, FACP, Fellow AIMBE, to determine whether BGMs on the market meet regulatory standards. The meeting consisted of four sessions in which Food and Drug Administration diabetes experts as well as leading academic clinicians and clinical chemists participated: (1) How is BGM performance determined? (2) Do approved BGMs perform according to International Organization for Standardization standards? (3) How do approved BGMs perform when used by patients and healthcare professionals? (4) What could be the consequence of poor BGM performance?
modeling analysis on the impact on hypoglycemic episodes, glycosylated hemoglobin (HbA1c), and, subsequently, myocardial infarctions; and (4) costs of diabetes-related complications in Germany. A reduction of meter error from 20% to 5% was identified to be associated with a 10% reduction in severe hypoglycemic episodes and a 0.39% reduction in HbA1c, which translates into a 0.5% reduction of myocardial infarctions.
Comment Moving forward, the topic of blood glucose strip accuracy is one of the most important concerns in the field. In the United States, the introduction of ‘‘competitive bidding’’ from nontraditional (or ‘‘off-brand’’) glucose test manufacturers has resulted in studies showing unacceptable accuracy. The regulatory ‘‘loopholes’’ of how these strips get onto the market and then stay on the market are a major concern for both providers and patients alike. Hopefully, these issues will be resolved in the near future.
Comment A ‘‘modeling analysis’’ is full of potential errors from assumptions that are potentially not valid. Nevertheless, this study suggests surprising and substantial cost savings with improvements of blood glucose meter accuracy. Perhaps more importantly, improvements in overall quality of health need to be appreciated. A true randomized trial comparing different meters with different accuracies is unlikely to be performed.
Results According to the health economic analysis, the reduction in severe hypoglycemic episodes and myocardial infarctions led to cost savings of e24.14 per patient per year. Considering 390,000 type 1 diabetes patients or 2.3 million insulin-treated patients in Germany, these savings could be equal to a reduction in healthcare expenditures of more than e9.4 million and e55.5 million, respectively. Conclusion Potential cost savings and clinical effects due to higher accuracy of BG meters should provide an impetus to implement tighter accuracy standards and develop glucose meters that provide highest possible accuracy.
Higher accuracy of self-monitoring of blood glucose in insulin-treated patients in Germany: clinical and economical aspects
Evaluation of a blood glucose monitoring system with automatic high- and low-pattern recognition software in insulin-using patients: pattern detection and patient-reported insights
Schnell O 1, Erbach M 2, Wintergerst E 3
Grady M 1, Campbell D 1, MacLeod K 1, Srinivasan A2
1
1
Forschergruppe Diabetes e.V., Helmholtz Center Munich, Munich-Neuherberg, Germany; 2Sciarc Institute, Baierbrunn, Germany; and 3Bayer Healthcare Diabetes Care, Basel, Switzerland
LifeScan Scotland Ltd., Inverness, UK; 2LifeScan, Inc., Milpitas, CA
J Diabetes Sci Technol 2013; 7: 970–78 Comment in: J Diabetes Sci Technol 2013; 7: 979–82
J Diabetes Sci Technol 2013; 7: 904–12
Background Background Accuracy standards of blood glucose (BG) meters are currently under review. Revised standards are expected to tighten accuracy requirements. Regarding clinical and financial impact of BG meter accuracy, very little data are available. This study analyzed the potential cost savings related to higher accuracy of glucose meters in Germany. Methods As a model for calculation, a reduction of meter error from 20% to 5% was applied. The health economic analysis was based on four main pillars: (1) number of insulin-treated patients; (2) costs for glucose monitoring in Germany; (3) data of a
This study aimed to evaluate the performance of a glucose pattern recognition tool incorporated in a blood glucose monitoring system (BGMS) and its association with clinical measures, and to assess user perception and understanding of the pattern messages they receive. Methods Participants had type 1 or type 2 diabetes mellitus and were self-adjusting insulin doses for ‡1 year. During a 4-week home testing period, participants performed ‡ 6 daily selftests, adjusted their insulin regimen based on BGMS results, and recorded pattern messages in the logbook. Participants reflected on usability of the pattern tool in a questionnaire.
SELF-MONITORING OF BLOOD GLUCOSE
S-11
Results
Conclusions
Study participants (N = 101) received a mean – standard deviation of 4.5 – 1.9 pattern messages per week (3.6 – 1.8 high glucose patterns and 0.9 – 1.3 low glucose patterns). Most received ‡ 1 high (96.5%) and/or ‡ 1 low (46.0%) pattern message per week. The average number of high- and low-pattern messages per week was associated with higher and lower, respectively, baseline hemoglobin A1c ( p < 0.01) and fasting plasma glucose ( p < 0.05). Participants found high- and low-pattern messages clear and easy to understand (84.2% and 83.2%, respectively) and considered the frequency of low (82.0%) and high (63.4%) pattern messages about right. Overall, 71.3% of participants preferred to use a meter with pattern messages.
SMBG continues to be an integral part of day-to-day management for people with type 1 diabetes and insulinrequiring patients with type 2 diabetes. Since CGMs are only approved as adjunctive, the role of SMBG in calibrating CGMs and cross-checking the glucose values with SMBG before acting on CGM values is indicated. Fortunately, the cost of SMBG strips is coming down, and we hope that it does not jeopardize further development of better technology for accurate SMBG strips. It is important to keep in mind that SMBG results in better health outcomes (improved A1c values) only if patients are advised on what to do with the SMBG values, and thus the role of education in the use of SMBG data is most important.
Conclusion The on-device Pattern tool identified meaningful blood glucose patterns, highlighting potential opportunities for improving glycemic control in patients who self-adjust their insulin.
Author Disclosure Statement No competing financial interests exist.
Comment As we are well into the era of ‘‘smart phones,’’ ‘‘smart watches,’’ and even ‘‘smart insulin pumps,’’ it seems that we certainly should have better technology for helping patients with real-time pattern recognition. Pattern messaging from glucose meters (or CGM devices) should be the standard of care, especially if studies continue to show good acceptance, improvements of A1C, and reductions of hypoglycemia.
References 1. Raskin P. The Somogyi phenomenon: sacred cow or bull? Arch Intern Med 1984; 144: 784–87. 2. Kovatchev BP, Cox DJ, Gonder-Frederick LA, et al. Assessment of risk for severe hypoglycemia among adults with IDDM: Validation of the low blood glucose index. Diabetes Care 1998; 21: 1870–75.
