METHODS: A retrospective observational study of 60 type 1 and 100 type 2 diabetes subjects. All underwent professional continuous glucose monitoring (CGM) for 3-6 days and recorded self-monitored blood glucose (SMBG). Indices were calculated from both CGM and SMBG. Statistical analyses included regression and area under receiver operator curve (AUC) analyses.
RESULTS: Hypoglycemia frequency (53.3% vs. 24%, P type 1 diabetes compared with type 2 diabetes. HbA1c was, at best, a weak predictor of hypoglycemia. %CVCGM, Low Blood Glucose Index (LBGI)CGM, Glycemic Risk Assessment Diabetes Equation (GRADE)HypoglycemiaCGM, and Hypoglycemia IndexCGM predicted hypoglycemia well. %CVCGM and %CVSMBG consistently remained a robust discriminator of hypoglycemia in type 1 diabetes (AUC 0.88). In type 2 diabetes, a combination of HbA1c and %CVSMBG or LBGISMBG could help discriminate hypoglycemia.
CONCLUSION: Assessment of glycemia should go beyond HbA1c and incorporate measures of GV and glycemic indices. %CVSMBG in type 1 diabetes and LBGISMBG or a combination of HbA1c and %CVSMBG in type 2 diabetes discriminated hypoglycemia well. In defining hypoglycemia risk using GV and glycemic indices, diabetes subtypes and data source (CGM vs. SMBG) must be considered.
MATERIALS AND METHODS: Seventy-four participants, with type 1 (T1D, n = 24), type 2 (T2D, n = 11), or gestational (n = 39) diabetes, were enrolled across 13 sites (9 in United Kingdom, 4 in Austria). Average gestation was 26.6 ± 6.8 weeks (mean ± standard deviation), age was 30.5 ± 5.1 years, diabetes duration was 13.1 ± 7.3 years for T1D and 3.2 ± 2.5 years for T2D, and 49/74 (66.2%) used insulin to manage their diabetes. Sensors were worn for up to 14 days. Sensor glucose values (masked) were compared with capillary SMBG values (made at least 4 times/day).
RESULTS: Clinical accuracy of sensor results versus SMBG results was demonstrated, with 88.1% and 99.8% of results within Zone A and Zones A and B of the Consensus Error Grid, respectively. Overall mean absolute relative difference was 11.8%. Sensor accuracy was unaffected by the type of diabetes, the stage of pregnancy, whether insulin was used, age or body mass index. User questionnaires indicated high levels of satisfaction with sensor wear, system use, and comparison to SMBG. There were no unanticipated device-related adverse events.
CONCLUSIONS: Good agreement was demonstrated between the FreeStyle Libre System and SMBG. Accuracy of the system was unaffected by patient characteristics, indicating that the system is safe and accurate to use by pregnant women with diabetes.
OBJECTIVE: To investigate prevalence and predictors of PREM defined by IDAA1c.
METHODS: Six hundred fourteen of 678 children (aged <15 years) with new-onset T1D (2000-2013) from a regional pediatric diabetes service (Auckland, New Zealand).
RESULTS: Overall rate of PREM at 3 months was 42.4%, and lower in Māori/Pacific children (28.6%; P = .006) and those of other ethnicities (28.8%; P = .030) compared with New Zealand Europeans (50.4%). Comparing the most and least deprived socioeconomic quintiles, the odds of PREM were lower among the most deprived (adjusted odds ratio [aOR] 0.44; P = .019). Lower rates of PREM were seen in children aged 0 to 4.9 years (23.8%) and 10 to 14 years (40.9%) than in children aged 5 to 9.9 years (57.4%; P
METHODS: We used data from the KARolinska MAmmography (Karma) project, a Swedish mammography screening cohort. Insulin-treated patients with type 1 (T1D, n = 122) and type 2 (T2D, n = 237) diabetes were identified through linkage with the Prescribed Drug Register and age-matched to 1771 women without diabetes. We assessed associations with treatment duration and insulin glargine use, and we further examined MD differences using non-insulin-treated T2D patients as an active comparator. MD was measured using a fully automated volumetric method, and analyses were adjusted for multiple potential confounders. Associations with the insulin genetic score were assessed in 9437 study participants without diabetes.
RESULTS: Compared with age-matched women without diabetes, insulin-treated T1D patients had greater percent dense (8.7% vs. 11.4%) and absolute dense volumes (59.7 vs. 64.7 cm3), and a smaller absolute nondense volume (615 vs. 491 cm3). Similar associations were observed for insulin-treated T2D, and estimates were not materially different in analyses comparing insulin-treated T2D patients with T2D patients receiving noninsulin glucose-lowering medication. In both T1D and T2D, the magnitude of the association with the absolute dense volume was highest for long-term insulin therapy (≥ 5 years) and the long-acting insulin analog glargine. No consistent evidence of differential associations by insulin treatment duration or type was found for percent dense and absolute nondense volumes. Genetically predicted insulin levels were positively associated with percent dense and absolute dense volumes, but not with the absolute nondense volume (percentage difference [95% CI] per 1-SD increase in insulin genetic score = 0.8 [0.0; 1.6], 0.9 [0.1; 1.8], and 0.1 [- 0.8; 0.9], respectively).
CONCLUSIONS: The consistency in direction of association for insulin treatment and the insulin genetic score with the absolute dense volume suggest a causal influence of long-term increased insulin exposure on mammographic dense breast tissue.