Self-monitoring of blood glucose

Abstract

Diabetes prevalence is increasing globally especially in the Asian subcontinent. It is expected that by the year 2030 there may be close to 400 million people with diabetes. All of the research in the past 25 years has clearly documented the effectiveness of improving glucose control in reducing long-term complications of diabetes, both microvascular and macrovascular. The improvement in glucose control usually requires continuous intensive diabetes management, particularly in insulin-requiring patients, which must include home self-monitoring of blood glucose (SMBG). Despite the convincing evidence, the role of SMBG in diabetes management is still being debated even though its availability in the past 35 years has revolutionised diabetes care, especially at home. The International Diabetes Federation (IDF) recently published guidelines for SMBG use in non-insulin-treated diabetic patients, recommending that SMBG should be used only when patients and/or their clinicians possess the ability, willingness and knowledge to incorporate SMBG and therapy adjustment into their diabetes care plan. The IDF also recommends that structured SMBG be performed with the choice of applying different defined blood glucose testing algorithms to patients’ individual diabetes care plans. These defined blood glucose testing algorithms give SMBG a medically meaningful structure to collect high quality glucose information and are called structured SMBG. Former SMBG studies have demonstrated SMBG to be beneficial when patients receive feedback regarding the impact of their behaviours on SMBG results. Other studies which did not link SMBG results to these principal behaviours have shown no SMBG benefit. A new wave of clinical studies performed after the release of the IDF guideline have recently been published and have proved the success of the new application of SMBG. The reasons for this ongoing debate may in part be due to rising healthcare costs globally, lack of convincing data in non-insulin-requiring patients with type 2 diabetes in randomised controlled clinical trials and multiple controversial meta-analyses performed on several studies. Sometimes the decisions are extended to insulin-requiring patients, even those with type 1 diabetes. For example, last year in the state of Washington in the USA, legislators were going to stop reimbursing glucose test strips for children with type 1 diabetes. After much debate with committee members (who were not diabetologists and or endocrinologists) and law makers, not only SMBG but even in some cases continuous glucose monitoring (CGM) is now reimbursed. The issue was simply educating non-understanding but well-meaning people whose main concern is saving money. In the end, no one, even those not familiar with paediatric type 1 diabetes, can disagree about the need for SMBG in this age group. It seems to us that we should instead be spending our time and effort in advancing the field and improving diabetes management for patients through newer technologies like CGM and closed-loop systems. As discussed in the section on CGM (Chapter 2) there is ample data from both non-randomised and randomised clinical trials showing the efficacy in reducing time spent in hypoglycaemia and hyperglycaemia along with improvement in glucose control without introducing any additional medication. We hope that the future will be spent in advancing the care rather than useless meta-analyses or going back in time. It is worthwhile to review existing evidence about SMBG to learn, transfer and apply knowledge about the core requirement for good diabetes management, glucose information. Fendler W, Hogendorf A, Szadkowska A, Młynarski W Department of Pediatrics, Oncology, Hematology and Diabetology, Medical University of Lodz, Poland Pediatr Endocrinol Diabetes Metab 2011; 17 : 57–63 Background: SMBG is one of the major components of diabetes management. Aims: To evaluate the potential for miscoding of a personal glucometer, to define a target population among paediatric patients with diabetes for a non-coding glucometer and to assess the accuracy of the Contour TS non-coding system. Methods: Potential for miscoding during SMBG was evaluated by means of an anonymous questionnaire, with worst and best case scenarios evaluated depending on the response pattern. Testing of the Contour TS system was performed according to the national committee for clinical laboratory standards guidelines. Results: The estimated frequency of individuals prone to non-coding ranged from 68.21% [95% confidence interval (CI) 60.70%–75.72%] to 7.95% (95% CI 3.86%–12.31%) for the worse and best case scenarios, respectively. Factors associated with increased likelihood of non-coding were a smaller number of tests per day, a greater number of individuals involved in testing and self-testing by the patient. The Contour TS device showed intra- and inter-assay accuracy of –95%, a linear association with laboratory measurements (R2 = 0.99, p < 0.0001) and small bias of –1.12% (95% CI –3.27% to 1.02%). Clarke error grid analysis showed 4% of values within the benign error zone (B) with the other measurements yielding an acceptably accurate result (zone A). Conclusions: The Contour TS system showed sufficient accuracy to be safely used in the monitoring of paediatric patients with diabetes. Patients from families with a high throughput of test-strips or multiple individuals involved in SMBG using the same meter are candidates for clinical use of such devices due to an increased risk of calibration errors. Comment: This study further highlights the role of making SMBG simpler and easier so that patients can monitor the glucose more effectively. The current study used the Contour TS system which does not require coding by the patient and thus removes the barrier of mis-coding of SMBG. We personally think that all meters going forward must be non-coding meters. Nerhus K 1 , Rustad P 2 , Sandberg S 1,3 1 Norwegian Centre for Quality Improvement of Primary Care Laboratories, Department of Public Health and Primary Health Care, University of Bergen, Bergen, Norway, 2 Norwegian Clinical Chemistry EQA-Program, Fürst Medical Laboratory, Oslo, Norway, 3 Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway Diabetes Technol Ther 2011; 13: 883–92 Background: Analytical quality of SMBG can be affected by environmental conditions. Aims: To determine the influence of a shift in the ambient temperature immediately before measurement and taking measurements in the lower and upper part of the operating temperature range. Methods: Different SMBG systems (n = 9) available on the Norwegian market were tested with heparinised venous blood (4.8 and 19.0 mmol/l). To test the effect of a shift in ambient temperature, the glucometer and strips were equilibrated for 1 h at 5 °C or 30 °C before the meter and strips were moved to room temperature, and measurements were performed after 0, 5, 10, 15 and 30 min. To test the lower and upper temperature range, measurements were performed at 10 °C and at 39 °C after 1 h for temperature equilibration of the glucometer and strips. All the measurements were compared with measurements performed simultaneously on a meter and strips kept the whole time at room temperature. Results: Six of nine SMBG systems overestimated and/or underestimated results by more than 5% after moving meters and strips from 5 °C or 30 °C to room temperature immediately before the measurements. Two systems underestimated the results at 10 °C. One system overestimated and another underestimated the results by more than 5% at 39 °C. Conclusions: A rapid shift in the ambient temperature affects analytical performance. Therefore patients need to wait at least 15 min for temperature equilibration of affected meters and strips before measuring blood glucose. Comment: This study highlights the importance of ambient temperature on analytical performance of SMBG. The study shows that rapid shift in ambient temperature may affect the accuracy and bias in SMBG measurement and highlights the need for 15 min temperature equilibration. In addition to what has been highlighted in the study, future studies also need to assess the accuracy of existing meters (especially the one using glucose oxidase) at higher altitudes (10,000 feet or higher). It is known that many of these meters do not perform well at high altitudes. McAndrew LM 1,2 , Horowitz CR 3 , Lancaster KJ 4 , Quigley KS 2,5,6 , Pogach LM 1,2 , Mora PA 7 , Leventhal H 8 1 War Related Illness and Injury Study Center and REAP Center for Healthcare Knowledge Management, Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA, 2 University of Medicine and Dentistry of New Jersey, Newark, NJ, USA, 3 Department of Health Evidence and Policy, Mount Sinai School of Medicine,New York, NY, USA, 4 Department of Nutrition, Food Studies and Public Health, New York University, New York, NY, USA, 5 Department of Veterans Affairs, Edith Nourse Rogers Memorial VA Hospital, Bedford, MA, USA, 6 Department of Psychology, Northeastern University, Boston, MA, USA, 7 Psychology Department, University of Texas at Arlington, Arlington, TX, USA, and 8 Institute for Health, Health Care Policy and Research, Rutgers University, New Brunswick, NJ, USA J Diabetes 2011; 3 : 147–52; Comment in J Diabetes 2011; 3 : 93–4 Background: It is unknown whether SMBG can motivate adherence to dietary recommendations. Aims: To evaluate if patients who used more SMBG would also report lower fat and greater fruit and vegetable consumption. Methods: This was a cross-sectional study of primarily minority individuals living with diabetes in East Harlem, New York (n = 401). Fat intake and fruit and vegetable consumption were measured with the Block Fruit/Vegetable/Fiber and Fat Screeners. Results: Greater frequency of SMBG was associated with lower fat intake [r(s) = –0.15; p < 0.01], but not fruit and vegetable consumption. The effects of SMBG were not moderated by insulin use. A significant interaction was found between frequency of SMBG and changing one’s diet in response to SMBG on total fat intake. Conclusions: The frequency of SMBG was associated with lower fat intake. The data suggest that participants who use SMBG to guide their diet do not have to monitor multiple times a day to benefit. Comment: This study further highlights the importance of SMBG in daily lifestyle changes. Subjects with higher frequency of SMBG consumed less fat, in part related to overall education and seeing the impact from making dietary changes on SMBG levels. Kuo CY 1,2 , Hsu CT 3 , Ho CS 3 , Su TE 3 , Wu MH 4 , Wang CJ 2,5 1 Department of Clinical Laboratory, Tai-An Hospital, Taichung, Taiwan, 2 Institute of Biochemistry and Biotechnology, Chung Shan Medical University, Taichung, Taiwan, 3 Department of Core Technical Research, Bionime Corporation, Taichung, Taiwan, 4 Department of Laboratory Medicine, Min-Sheng General Hospital, Taoyuan, Taiwan, 5 Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan Diabetes Technol Ther 2011; 13 : 596–600 Background: SMBG systems should at least meet the minimal requirement of the World Health Organization’s ISO 15197:2003. For tight glycaemic control, a tighter accuracy requirement is needed. Methods: Seven SMBG systems were evaluated for accuracy and precision: Bionime Rightest™ GM550 (Bionime Corp., Dali City, Taiwan), Accu-Chek® Performa (Roche Diagnostics, Indianapolis, IN, USA), OneTouch® Ultra®2 (LifeScan Inc., Milpitas, CA, USA), MediSense® Optium™ Xceed (Abbott Diabetes Care Inc., Alameda, CA, USA), Medisafe (TERUMO Corp., Tokyo, Japan), Fora® TD4227 (Taidac Technology Corp., Wugu Township, Taiwan) and Ascensia Contour® (Bayer HealthCare LLC, Mishawaka, IN, USA). The 107 participants were 23–91 years old. The analytical results of seven SMBG systems were compared with those of plasma analysed with the hexokinase method (Olympus AU640, Olympus America Inc., Center Valley, PA, USA). Results: The imprecision of the seven blood glucose meters ranged from 1.1% to 4.7%. Three of the seven blood glucose meters (42.9%) fulfilled the minimum accuracy criterion of ISO 15197:2003. The mean absolute relative error value for each blood glucose meter was calculated and ranged from 6.5% to 12.0%. Conclusions: More than 40% of evaluated SMBG systems meet the minimal accuracy criterion requirement of ISO 15197:2003. However, considering a tighter criterion for accuracy of ±15%, only the Bionime Rightest GM550 meets this requirement. Manufacturers have to try to improve accuracy and precision and to ensure the good quality of blood glucose meters and test strips. Comment: This study further highlights the need for more accurate SMBG systems. Their data concluded that more than 40% of the evaluated SMBG systems meet the minimum ISO criteria. Since patients use blood glucose information for adjusting their insulin dose and/or treating hypoglycaemia, the accuracy of the glucose meters has to be consistent and improved. Hortensius J 1 , Slingerland RJ 2 , Kleefstra N 1,3,4 , Logtenberg SJ 1 , Groenier KH 5 , Houweling ST 3,6 , Bilo HJ 1,4 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Medical Research Group, Langerhans, The Netherlands, 4 Department of Internal Medicine, University Medical Center, Groningen, The Netherlands, 5 Department of General Practice, University of Groningen, Groningen, The Netherlands, and 6 General Practice Sleeuwijk, Sleeuwijk, The Netherlands Diabetes Care 2011; 34 : 556–60 Background: There is no agreement regarding the use of the first or second drop of blood for glucose monitoring. Aims: To investigate whether capillary glucose concentrations, as measured in the first and second drops of blood, differed ≥10% compared with a control glucose concentration in different situations. Methods: Capillary glucose concentrations were measured in two consecutive drops of blood in 123 patients with diabetes in the following circumstances: without washing hands, after exposing the hands to fruit, after washing the fruit-exposed hands, and during application of different amounts of external pressure around the finger. The results were compared with control measurements. Results: Not washing hands led to a difference of ≥10% in glucose concentration in the first and in the second drops of blood in 11% and 4% of the participants, respectively. In fruit exposed fingers, these differences were found in 88% and 11% of the participants, respectively. Different external pressures led to ≥10% differences in glucose concentrations in 5%–13% of the participants. Conclusions: Washing hands with soap and water, drying them, and using the first drop of blood for SMBG is recommended. If washing hands is not possible, it is acceptable to use the second drop of blood after wiping away the first drop. External pressure may lead to unreliable readings. Comment: Over the years we have probably under-emphasised the importance of technique with SMBG. One has to wonder how much iatrogenic hypoglycaemia has occurred due to unintended exposure to glucose on the hands, and how often CGM devices are inaccurate due to poor technique with SMBG use. Polonsky WH 1,2 , Fisher L 3 , Schikman CH 4 , Hinnen DA 5 , Parkin CG 6 , Jelsovsky Z 7 , Petersen B 8 , Schweitzer M 8 , Wagner RS 8 1 University of California, San Diego, CA, USA, 2 Behavioral Diabetes Institute, San Diego, CA, USA, 3 University of California, San Francisco, CA, USA, 4 North Shore University Health System, Skokie, IL, USA, 5 Mid America Diabetes Associates, Wichita, KS, USA, 6 Health Management Resources, Carmel, IN, USA, 7 Biostat International, Tampa, FL, USA, and 8 Roche Diagnostics, Indianapolis, IN, USA Diabetes Care 2011; 34 : 262–7 Aim: To assess the effectiveness of structured blood glucose testing in poorly controlled patients with type 2 diabetes without insulin treatment. Methods: A 12-month prospective, randomised, multicentre study recruited insulin-naive patients with type 2 diabetes (n = 483) and poor glycaemic control (A1C ≥ 7.5%) from 34 primary care practices in the USA. Practices were randomised to an active control group (ACG) with enhanced usual care or a structured testing group (STG) with enhanced usual care and at least quarterly use of structured SMBG. STG patients and physicians were trained to use a paper tool to collect/interpret seven-point glucose profiles over three consecutive days. The primary endpoint was HbA1c level measured at 12 months. Results: The 12-month intent-to-treat analysis (ACG, n = 227; STG, n = 256) showed significantly greater reductions in mean (SE) HbA1c in the STG compared with the ACG [–1.2% (0.09) vs. –0.9% (0.10); Δ = –0.3%; p = 0.04]. Per-protocol analysis (ACG, n = 161; STG, n = 130) showed even greater mean (SE) HbA1c reductions in the STG compared with the ACG [–1.3% (0.11) vs. –0.8% (0.11); Δ= –0.5%; p < 0.003]. Significantly more STG patients received a treatment change recommendation at the first month visit compared with ACG patients, regardless of the patient’s initial baseline HbA1c level (75.5% vs. 28.0%; p < 0.0001). Both STG and ACG patients displayed significant (p < 0.0001) improvements in general well-being. Conclusions: Appropriate use of structured SMBG significantly improves glycaemic control and facilitates more timely/aggressive treatment changes in insulin-naive patients with type 2 diabetes without decreasing general well-being. Comment: It is clear that, with an engaged healthcare team, using a structured glucose testing strategy can improve glucose control in non-insulin-treated patients. Potential benefits are many, including cost of care. Whether this can be repeated in a non-study setting with the more typical time limits encountered in a primary care setting remains to be seen. Lyon ME 1,2,3,4 , DuBois JA 5 , Fick GH 6 , Lyon AW 1,4 1 Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada, 2 Department of Pharmacology and Physiology, University of Calgary, Calgary, AB, Canada, 3 Department of Pediatrics, University of Calgary, Calgary, AB, Canada, 4 Calgary Laboratory Services, Calgary, AB, Canada, 5 Nova Biomedical Corporation, Waltham, MA, USA, and 6 Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada J Diabetes Sci Technol 2010; 4 : 1479–94 Aims: To estimate analytical error in consumer and hospital glucose meters contributed by variations in haematocrit, maltose, ascorbate and imprecision. Methods: The influences of haematocrit (20%–60%), maltose and ascorbate were tested alone and in combination with each glucose meter and with a reference plasma glucose method at three glucose concentrations. Precision was determined by consecutive analysis (n = 20) at three glucose levels. Multivariate regression analysis was used to estimate the bias associated with the interferences, alone and in combination. Results: Three meters demonstrated haematocrit bias that was dependent upon glucose concentration. Maltose had profound concentration-dependent positive bias on the consumer meters, and the extent of maltose bias was dependent on haematocrit. Ascorbate produced small statistically significant biases on three meters. Coincident low haematocrit, presence of maltose and presence of ascorbate increased the observed bias and was summarised by estimation of total analytical error. Among the four glucose meter devices assessed, estimates of total analytical error in glucose measurement ranged from 6% to 68% under the conditions tested. Conclusions: The susceptibility of glucose meters to clinically significant analytical biases is highly device-dependent. Low haematocrit exacerbated the observed analytical error. Comment: Concerns continue with regard to interferences for SMBG devices, and although the research is consistent, it does not appear that many people appreciate the various problems. This has particular impact on hospitalised patients. Furthermore, as new guidelines for transfusion (allowing greater degrees of anaemia) are implemented, the impact on SMBG accuracy could be profound. Better educational programmes, particularly by the device manufacturers, should be a priority. Pollock RF 1 , Valentine WJ 1 , Goodall G 2 , Brandle M 3 1 Ossian Health Economics and Communications, Basel, Switzerland, 2 IMS Health, Basel, Switzerland, and 3 Division of Endocrinology and Diabetes, Department of Internal Medicine, Kantonsspital, St Gallen, Switzerland Swiss Med Wkly 2010; 140 : w13103 Aims: To evaluate the cost-effectiveness of SMBG in patients with type 2 diabetes treated with oral antidiabetic agents (OADs) in Switzerland. Methods: In a large observational study a validated computer model of diabetes was used to project outcomes reported from a published longitudinal study of SMBG in patients with type 2 diabetes, treated with OADs and with no history of SMBG, over a 30-year time horizon. Cost-effectiveness was assessed from the perspective of a third party healthcare payer. Costs and clinical outcomes were discounted at 3% annually. Results: Once, twice or three times daily SMBG was associated with improvements in HbA1c which led to increased life expectancy and quality-adjusted life expectancy and reduced incidence of diabetes complications compared with no SMBG in type 2 diabetes patients on OADs. Direct medical costs increased by CHF 528, CHF 1650 and CHF 2899 in patients performing SMBG once, twice or three times daily respectively compared with those not using SMBG. Incremental cost-effectiveness ratios were well below commonly quoted willingness-to-pay thresholds at CHF 9,177, CHF 12,928 and CHF 17,342 per quality-adjusted life year gained, respectively. Conclusions: SMBG is likely to be cost-effective by generally accepted standards in SMBG-naive patients on OADs in the Swiss setting. Comment: This interesting analysis is based on a ‘validated computer model’ showing improvements of HbA1c, life expectancy and quality-adjusted life year. The concern of course is that this analysis is not a real randomised controlled trial, and while at best the data are mixed about the efficacy of this population using SMBG, this particular analysis is probably based on controversial assumptions. Carroll AE 1,2 , DiMeglio LA 3 , Stein S 3 , Marrero DG 2,4 1 Children’s Health Services Research, Indiana University School of Medicine, Indianapolis, IN, USA, 2 Regenstrief Institute for Health Care, Indianapolis, IN, USA, 3 Section of Pediatric Endocrinology, Indiana University School of Medicine, Indianapolis, IN, USA, and 4 Diabetes Prevention and Control Center, Indiana University School of Medicine, Indianapolis, IN, USA Diabetes Educ 2011; 37 : 59–66 Aim: To assess the feasibility and acceptability of a cell phone glucose monitoring system for adolescents with type 1 diabetes and their parents. Methods: Patients with type 1 diabetes who had been diagnosed for at least 1 year participated in the study. Each adolescent used the system for 6 months, filling out surveys every 3 months to measure usability and satisfaction with the cell phone glucose monitoring system, as well as how use of the system might affect quality of family functioning and diabetes management. Results: Adolescents reported positive feelings about the technology, although a large number of them had significant technical issues that affected continued use of the device. Nearly all thought that the clinic involvement in monitoring testing behaviour was acceptable. The use of the Glucophone™ did not change the adolescent’s quality of life, their level of conflict with their parents, their reported self-management of diabetes, or their average glycaemic control within the short time frame of the study. Conclusions: This work demonstrates that cell phone glucose monitoring technology can be used in an adolescent population to track and assist in self-monitoring behaviour. Comment: Mobile technology for both SMBG and CGM is clearly the future for adolescents (and adults) with type 1 diabetes. The real challenge will be to learn how to best use this technology to improve diabetes-related outcomes in this population. To date, the technology is too new to know how best to use it. Many more studies will be required to answer this question. de Mol P 1 , Krabbe HG 2 , de Vries ST 3 , Fokkert MJ 2 , Dikkeschei BD 2 , Rienks R 4 , Bilo KM 5 , Bilo HJ 5,6 1 Department of Internal Medicine, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Department of Cardiology, Isala Clinics, Zwolle, The Netherlands, 4 Centre for Human Aviation, Dutch Airforce, Soesterberg, The Netherlands, 5 Department of Internal Medicine, Isala Clinics, Zwolle, The Netherlands, and 6 Department of Internal Medicine, University Medical Centre, Groningen, The Netherlands PLoS One 2010; 5 : e15485 Background: Patients with diabetes take part in extreme sports (e.g. high-altitude trekking), and thus reliable handheld blood glucose meters (BGMs) are necessary. Prior studies reported bias in blood glucose measurements using different BGMs at high altitude. Aim: To evaluate if glucose oxidase based BGMs are more influenced by the lower atmospheric oxygen pressure at altitude than glucose dehydrogenase based BGMs. Methods: Glucose measurements at simulated altitude of nine BGMs (six glucose dehydrogenase, three glucose oxidase BGMs) were compared with glucose measurement on a similar BGM at sea level and with a laboratory glucose reference method. Venous blood samples of four different glucose levels were used. Accuracy criteria were set at a bias <15% from reference glucose (when >6.5 mmol/l) and <1 mmol/l from reference glucose (when <6.5 mmol/l). Results: No significant difference was observed between measurements at simulated altitude and sea level for either glucose oxidase based BGMs or glucose dehydrogenase based BGMs as a group phenomenon. Two glucose dehydrogenase based BGMs did not meet set performance criteria. Conclusions: At simulated high altitude all tested BGMs, including glucose oxidase based BGMs, did not show influence of low atmospheric oxygen pressure. All BGMs, except for two glucose dehydrogenase based BGMs, performed within predefined criteria. Most BGMs are generally overestimating true glucose concentration at high altitude. At true high altitude one glucose dehydrogenase based BGM had best precision and accuracy. Comment: Simulated altitude testing for SMBG meters may be problematic. In general, glucose oxidase test strips should be avoided at high altitudes. Although not studied in this analysis, it should be noted that most patients do not take this into consideration when hiking or skiing. Harris LT 1 , Tufano J 2 , Le T 2 , Rees C 1 , Lewis GA 3 , Evert AB 4 , Flowers J 3 , Collins C 5 , Hoath J 6 , Hirsch IB 7 , Goldberg HI 7 , Ralston JD 8 1 Department of Health Services, University of Washington, Magnuson Health Sciences Center, Seattle, WA, USA, 2 Biomedical and Health Informatics, Department of Medical Education and Biomedical Informatics, University of Washington, Seattle, WA, USA, 3 Department of Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA, USA, 4 Diabetes Care Center, UW Medical Center-Roosevelt, WA, USA, 5 Department of Pharmaceutics, University of Washington, Seattle, WA, USA, 6 UW Medicine Information Technology Services, Northgate Executive Center II, Seattle, WA, USA, 7 Department of Medicine, University of Washington, Seattle, WA, USA, and 8 Group Health Research Institute, Seattle, WA, USA J Biomed Inform 2010; 43 (5 Suppl): S37–40 Aims: To assess the feasibility and acceptability of using mobile phones as part of an existing web-based system for collaboration between patients with diabetes and a primary care team. Methods: In design sessions, mobile wireless glucose meter uploads and two approaches to mobile-phone-based feedback on glycaemic control were tested. Results: Mobile glucose meter uploads combined with graphical and tabular data feedback were the most desirable system features tested. Participants had mixed reactions to an automated and tailored messaging feedback system for self-management support. Participants saw value in the mobile system as an adjunct to the web-based programme and traditional office-based care. Conclusions: Mobile diabetes management systems may represent one strategy to improve the quality of diabetes care. Comment: How best to integrate mobile technology in a primary care setting for type 2 diabetes is still unclear. It is quite likely that there will be different types of mobile technology that will work better for different patient populations. Still, the growing use of the mobile phone as a primary means of communication makes that device seem like the centre of attention in diabetes management. While the technology now seems to be available, how to get physicians interested is a separate challenge. It may be that separate reimbursements will be the only incentive for many physicians given the burden of time this population already generates. Hoffmann F 1 , Andersohn F 2 1 Centre for Social Policy Research, Division of Health Economics, Health Policy and Outcomes Research, University of Bremen, Bremen, Germany, and 2 Institute for Social Medicine, Epidemiology, and Health Economics, Charité University Medical Centre Berlin, Berlin, Germany Diabetologia 2011; 54 : 308–11 Background: Previously the observational Retrolective Study: Self-monitoring of Blood Glucose and Outcome in Patients with Type 2 Diabetes (ROSSO) reported a 51% reduction in the risk of all-cause mortality in patients with type 2 diabetes who performed SMBG. Aims: To evaluate if these findings are caused by a flawed design that introduced immortal time bias. Methods: The bias in the ROSSO study was illustrated and demonstrated that it is large enough to explain the apparently protective effect of SMBG on all-cause mortality. Results: In the ROSSO study, patients were classified as exposed to SMBG for their whole follow-up time if they performed SMBG for at least 1 year during the study period. Thus, the time between cohort entry and the date after 1 year of self-monitoring was performed is unavoidably ‘immortal’ for patients with SMBG. Patients had to survive at least 1 year to be classified as exposed to this intervention and were artificially ‘protected’ from death. The total amount of misclassified immortal person-time in the SMBG group is at least 5082 of 9248 person-years at risk (55%). After reclassification of immortal person-time as unexposed, the unadjusted relative risk changed from 0.59 to 1.95. Conclusions: The apparently protective effect of SMBG on all-cause mortality observed in the ROSSO study is completely explained by immortal time bias. Comment: The ROSSO study is one of the most-quoted trials in the area of SMBG. Study design is probably a major reason for non-agreement between the various studies. Kleefstra N 1,2 , Hortensius J 1 , Logtenberg SJ 1 , lingerland R 3 , Groenier K 4 , Houweling ST 2,5 , Gans RO 6 , van Ballegooie E 2 , Bilo HJ 1,6 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Medical Research Group Langerhans, Zwolle, The Netherlands, 3 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 4 Department of General Practice, University of Groningen, Groningen, The Netherlands, 5 General Practice Sleeuwijk, Sleeuwijk, The Netherlands, 6 Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands Neth J Med 2010; 68 : 311–6 Background: It is not clear if SMBG improves glycaemic control in insulin-naive patients with type 2 diabetes. Aim: To investigate the effects of SMBG in insulin-naive patients with type 2 diabetes who were in persistent moderate glycaemic control. Methods: Patients aged 18–70 years with an HbA1c level of 7%–8.5%, using one to two oral blood glucose lowering agents, were included in the study. Patients (n = 41) were randomly assigned to receive either SMBG added to usual care or to continue with usual care for 1 year. A fasting glucose value and three postprandial glucose values were measured twice weekly. The primary efficacy parameter was HbA1c. Health-related quality of life and treatment satisfaction were assessed using the Short-form 36 Health Survey Questionnaire (SF-36), the T2D Symptom Checklist (DSC-r), the Diabetes Treatment Satisfaction Questionnaire (DTSQ) and the WHO Wellbeing Index (WHO-5). Results: Change in HbA1c between groups was –0.05% (95% CI –0.51 to 0.41; p = 0.507). There were no significant changes between groups on the DTSQ, DSC type 2, WHO-5 or SF-36, except for the SF-36 dimension ‘health change’ which was lower in the SBMG group [mean difference –12 (95% CI –20.9 to –3.1)]. Conclusions: Tablet-treated type 2 diabetes patients experienced some worsening of their health perception. Thus, the use of SMBG in these patients is questionable, and its unlimited use should be reconsidered. Comment: This is another negative SMBG study in non-insulin-treated type 2 patients. While the criticism of not adequately teaching patients what to do with the information is quite valid, one has to wonder if this continued signal at some point needs to have some degree of acceptance. At the very least, it is difficult to argue that the average physician in primary care is able to provide more education and time than is done in many of these studies. Sonmez A 1 , Yilmaz Z 1 , Uckaya G 1 , Kilic S 2 , Tapan S 3 , Taslipinar A 1 , Aydogdu A 1 , YaziciM 1 , Yilmaz MI 4 , Serdar M 3 , Erbil MK 3 , Kutlu M 1 1 Department of Endocrinology and Metabolism, Gulhane School of Medicine, Ankara, Turkey, 2 Department of Epidemiology, Gulhane School of Medicine, Ankara, Turkey, 3 Department of Biochemistry, Gulhane School of Medicine, Ankara, Turkey, and 4 Department of Nephrology, Gulhane School of Medicine, Ankara, Turkey Diabetes Technol Ther 2010; 12 : 619–26 Background: Home glucose meters (HGMs) may not be accurate enough to sense hypoglycaemia. Aims: Evaluation of the accuracy and the capillary and venous comparability of five different HGMs [Optium Xceed (Abbott Diabetes Care, Alameda, CA, USA), Contour TS (Bayer Diabetes Care, Basel, Switzerland), Accu-Chek Go (Roche Ltd, Basel, Switzerland), OneTouch Select (Lifescan, Milpitas, CA, USA) and EZ Smart (Tyson Bioresearch Inc., Chu-Nan, Taiwan)] in an adult population. Methods: The insulin hypoglycaemia test was performed for 59 subjects of mean age 23.6 ± 3.2 years. Glucose was measured from venous blood and finger capillary samples before and after injection of regular insulin (0.1 U/kg). Venous samples were analysed in the reference laboratory by the hexokinase method. In vitro tests for method comparison and precision analyses were also performed by spiking the glucose-depleted venous blood. Results: All HGMs failed to sense hypoglycaemia to some extent. EZ Smart was significantly inferior in critical error zone D, and OneTouch Select was significantly inferior in the clinically unimportant error zone B. Accu-Chek Go, Optium Xceed and Contour TS had similar performances and were significantly better than the other two HGMs according to error grid analysis or International Organisation for Standardisation criteria. The in vitro tests were consistent with the above clinical data. The capillary and venous consistencies of Accu-Chek Go and OneTouch Select were better than the other HGMs. Conclusion: Not all HGMs are accurate enough in low blood glucose levels. The patients and the caregivers should be aware of these restrictions of the HGMs and give more credit to the hypoglycaemia symptoms than the values obtained with the HGMs. These results indicate that there is a need for the revision of accuracy standards of HGMs at low blood glucose levels. Comment: We have learned the hard way that today’s meters are far from perfect, especially at hypoglycaemic levels. Most patients can state a specific time when they received an inaccurate reading. The implications are obvious, not only for the treatment of hypoglycaemia but also as we move forward with CGM about how this problem impacts calibration. While correspondence about this paper questions the investigators’ compliance with the specific manufacturer’s recommendations for use of the meters (1), our clinical experience with patient error makes us believe that accuracy remains a tremendous problem for glucose meters at hypoglycaemic levels. SG has received research grants from Novo Nordisk, Sanofi-Aventis, Dexcom Inc., MannKind Corporation, Halozyme Therapeutics, Medtronic-MiniMed, Merck Inc., Daiichi Sankyo and Eli Lilly. IBH is a consultant for Roche Diagnostics, Abbott Diabetes Care and Johnson & Johnson.