OBJECTIVE -To determine whether a system of telemedicine support can improve glycemic control in type 1 diabetes. RESEARCH DESIGN AND METHODS-A 9-month randomized trial compared glucose self-monitoring real-time result transmission and feedback of results for the previous 24 h in the control group with real-time graphical phone-based feedback for the previous 2 weeks together with nurse-initiated support using a web-based graphical analysis of glucose selfmonitoring results in the intervention group. All patients aged 18 -30 years with HbA 1c (A1C) levels of 8 -11% were eligible for inclusion.RESULTS -A total of 93 patients (55 men) with mean diabetes duration (means Ϯ SD) 12.1 Ϯ 6.7 years were recruited from a young adult clinic. In total, the intervention and control groups transmitted 29,765 and 21,400 results, respectively. The corresponding median blood glucose levels were 8.9 mmol/l (interquartile range 5.4 -13.5) and 10.3 mmol/l (6.5-14.4) (P Ͻ 0.0001). There was a reduction in A1C in the intervention group after 9 months from 9.2 Ϯ 1.1 to 8.6 Ϯ 1.4% (difference 0.6% [95% CI 0.3-1.0]) and a reduction in A1C in the control group from 9.3 Ϯ 1.5 to 8.9 Ϯ 1.4% (difference 0.4% [0.03-0.7]). This difference in change in A1C between groups was not statistically significant (0.2% [Ϫ0.2 to 0.7, P ϭ 0.3).CONCLUSIONS -Real-time telemedicine transmission and feedback of information about blood glucose results with nurse support is feasible and acceptable to patients, but to significantly improve glycemic control, access to real-time decision support for medication dosing and changes in diet and exercise may be required. Diabetes Care 28:2697-2702, 2005T he incidence of type 1 diabetes in childhood has more than doubled in the past 2-3 decades (1). The proportion of patients with serious complications increases rapidly from late adolescence to early adulthood and has been reported to increase from 3 to 37% over 11 years, follow-up in the age-group 17-25 years (2). Tight glycemic control and intensive support has been shown to improve control and reduce the risk of retinopathy, neuropathy, and nephropathy by up to 75% (3). One method of improving outcomes in routine practice without substantially increasing resources may be to make use of appropriate technical innovations.Trials of telemedicine interventions in diabetes have demonstrated the feasibility and acceptability of systems for downloading glucose data, although no favorable impact on A1C has been shown consistently (4). Systems for computerized decision support have been evaluated (5,6), and other systems have recorded lifestyle and medication data (7) and provided telephone advice from a clinician (8,9). However, none incorporated real-time transfer of data to a remote computer system for data processing (4). Improved system functionality with realtime data transfer may lead to more effective use and improved control. We therefore conducted in a young adult population a randomized, controlled, clinical trial of a mobile phone-based telemedicine system using r...

OBJECTIVEMisdiagnosis of maturity-onset diabetes of the young (MODY) remains widespread, despite the benefits of optimized management. This cross-sectional study examined diagnostic misclassification of MODY in subjects with clinically labeled young adult-onset type 1 and type 2 diabetes by extending genetic testing beyond current guidelines.RESEARCH DESIGN AND METHODSIndividuals were selected for diagnostic sequencing if they displayed features atypical for their diagnostic label. From 247 case subjects with clinically labeled type 1 diabetes, we sequenced hepatocyte nuclear factor 1 α (HNF1A) and hepatocyte nuclear factor 4 α (HNF4A) in 20 with residual β-cell function ≥3 years from diagnosis (random or glucagon-stimulated C-peptide ≥0.2 nmol/L). From 322 with clinically labeled type 2 diabetes, we sequenced HNF1A and HNF4A in 80 with diabetes diagnosed ≤30 years and/or diabetes diagnosed ≤45 years without metabolic syndrome. We also sequenced the glucokinase (GCK) in 40 subjects with mild fasting hyperglycemia.RESULTSIn the type 1 diabetic group, two HNF1A mutations were found (0.8% prevalence). In type 2 diabetic subjects, 10 HNF1A, two HNF4A, and one GCK mutation were identified (4.0%). Only 47% of MODY case subjects identified met current guidelines for diagnostic sequencing. Follow-up revealed a further 12 mutation carriers among relatives. Twenty-seven percent of newly identified MODY subjects changed treatment, all with improved glycemic control (HbA1c 8.8 vs. 7.3% at 3 months; P = 0.02).CONCLUSIONSThe systematic use of widened diagnostic testing criteria doubled the numbers of MODY case subjects identified compared with current clinical practice. The yield was greatest in young adult-onset type 2 diabetes. We recommend that all patients diagnosed before age 30 and with presence of C-peptide at 3 years' duration are considered for molecular diagnostic analysis.

Telemedicine systems have been proposed as a means of supporting people with diabetes in the self-management of their condition. Requirements for monitoring parameters of care, including glycaemic control, extent of analysis and interpretation of data, patient-clinician contacts, and involvement of a multidisciplinary care team with effective communication, can be addressed by telemedicine systems. We describe the development and implementation of an innovative real-time telemedicine system based around transmission and feedback of data to and from a mobile phone. Proprietary Java-based programs were used to link a blood glucose meter to a mobile phone. In addition to immediate transmission of blood glucose data, information about insulin dose, eating patterns and physical exercise were collected. Immediate feedback to the phone included a colour histogram to draw attention to levels of control over glycaemia over the previous two weeks. Clinicians supporting patients had access to summary screens identifying users not testing, and those with levels of blood glucose outside pre-defined limits. More detailed graphical displays of data were used to provide data about control of insulin dose and the degree to which it was modified in response to diet and exercise. The system has been evaluated in a clinical trial conducted in secondary care and is now being adapted for use in a trial in primary care, which is designed to assess its effectiveness in providing integrated management for the patient, general practitioner and pharmacist.

OBJECTIVEAssignment of the correct molecular diagnosis in diabetes is necessary for informed decisions regarding treatment and prognosis. Better clinical markers would facilitate discrimination and prioritization for genetic testing between diabetes subtypes. Serum 1,5 anhydroglucitol (1,5AG) levels were reported to differentiate maturity-onset diabetes of the young due to HNF1A mutations (HNF1A-MODY) from type 2 diabetes, but this requires further validation. We evaluated serum 1,5AG in a range of diabetes subtypes as an adjunct for defining diabetes etiology.RESEARCH DESIGN AND METHODS1,5AG was measured in U.K. subjects with: HNF1A-MODY (n = 23), MODY due to glucokinase mutations (GCK-MODY, n = 23), type 1 diabetes (n = 29), latent autoimmune diabetes in adults (LADA, n = 42), and type 2 diabetes (n = 206). Receiver operating characteristic curve analysis was performed to assess discriminative accuracy of 1,5AG for diabetes etiology.RESULTSMean (SD range) 1,5AG levels were: GCK-MODY 13.06 μg/ml (5.74–29.74), HNF1A-MODY 4.23 μg/ml (2.12–8.44), type 1 diabetes 3.09 μg/ml (1.45–6.57), LADA 3.46 μg/ml (1.42–8.45), and type 2 diabetes 5.43 (2.12–13.23). Levels in GCK-MODY were higher than in other groups (P < 10−4 vs. each group). HNF1A-MODY subjects showed no difference in unadjusted 1,5AG levels from type 2 diabetes, type 1 diabetes, and LADA. Adjusting for A1C revealed a difference between HNF1A-MODY and type 2 diabetes (P = 0.001). The discriminative accuracy of unadjusted 1,5AG levels was 0.79 for GCK-MODY versus type 2 diabetes and 0.86 for GCK-MODY versus HNF1A-MODY but was only 0.60 for HNF1A-MODY versus type 2 diabetes.CONCLUSIONSIn our dataset, serum 1,5AG performed well in discriminating GCK-MODY from other diabetes subtypes, particularly HNF1A-MODY. Measurement of 1,5AG levels could inform decisions regarding MODY diagnostic testing.