Efficacy of a Smart Insulin Pen Cap for the Management of Patients with Uncontrolled Type 2 Diabetes: A Randomized Cross-Over Trial.

BACKGROUND: We studied a smart insulin pen cap that can be plugged to several brand of insulin pens, to track insulin administration via smart-phone Bluetooth technology, with alarm/reminder system aiming. METHODS: This pilot randomized, cross-over design study assessed the use of a smart insulin pen cap in improving adherence, glycemic control and patient satisfaction in insulin-treated patients with poorly controlled type 2 diabetes. Eighty patients on basal insulin ± oral agents with hemoglobin A1C (HbA1c) between 7.0% and 12.0% were randomized to a 12-week active phase receiving alarms/reminders and a 12-week control/masked phase without feedback. We assessed differences between groups on treatment adherence, insulin omission, and mistiming of insulin injections, HbA1c, treatment satisfaction (using Diabetes Treatment Satisfaction Questionnaire Status). RESULTS: Compared to the control/masked phase, the active phase resulted in lower mean daily blood glucose (147.0 ± 34 vs 157.6 ± 42 mg/dL, P < .01); and greater reduction in HbA1c from baseline (-0.98% vs -0.72%, P = .006); however, no significant differences in treatment adherence, insulin omission or insulin mistiming were observed. High patient satisfaction scores were reported in both active and control phases, with DTSQc of 15.5 ± 3.7 and 14.9 ± 3.6, respectively. Statistical models showed no residual effect after cross-over between active and control phases. CONCLUSIONS: The results of this pilot study indicates that this smart insulin pen cap was effective in improving glycemic control with overall good satisfaction in insulin treated patients with type 2 diabetes. Future studies are needed to confirm its potential for improving care in insulin treated patients with diabetes.

1-h Glucose During Oral Glucose Tolerance Test Predicts Hyperglycemia Relapse-Free Survival in Obese Black Patients With Hyperglycemic Crises.

Objective: Approximately 50% of obese Black patients with unprovoked diabetic ketoacidosis (DKA) or severe hyperglycemia (SH) at new-onset diabetes achieve near-normoglycemia remission with intensive insulin treatment. Despite the initial near-normoglycemia remission, most DKA/SH individuals develop hyperglycemia relapse after insulin discontinuation. Traditional biomarkers such as normal glucose tolerance at the time of remission were not predictive of hyperglycemia relapse. We tested whether 1-h plasma glucose (1-h PG) at remission predicts hyperglycemia relapse in Black patients with DKA/SH. Methods: Secondary analysis was performed of two prospective randomized controlled trials in 73 patients with DKA/SH at the safety net hospital with a median follow-up of 408 days. Patients with DKA/SH underwent a 5-point, 2-h 75-g oral glucose tolerance test after hyperglycemia remission. Hyperglycemia relapse is defined by fasting blood glucose (FBG) > 130 mg/dl, random blood glucose (BG) >180 mg/dl, or HbA1c > 7%. Results: During the median 408 (interquartile range: 110-602) days of follow-up, hyperglycemia relapse occurred in 28 (38.4%) participants. One-hour PG value ≥199 mg/dl discriminates hyperglycemia relapse (sensitivity: 64%; specificity: 71%). Elevated levels of 1-h PG (≥199 mg/dl) were independently associated with hyperglycemia relapse (adjusted hazard ratio: 2.40 [95% CI: 1.04, 5.56]). In a multivariable model with FBG, adding 1-h PG level enhanced the prediction of hyperglycemia relapse, with significant improvements in C-index (Δ: +0.05; p = 0.04), net reclassification improvement (NRI: 48.7%; p = 0.04), and integrated discrimination improvement (IDI: 7.8%; p = 0.02) as compared with the addition of 2-h PG (NRI: 20.2%; p = 0.42; IDI: 1.32%; p = 0.41) or HbA1c (NRI: 35.2%; p = 0.143; IDI: 5.8%; p = 0.04). Conclusion: One-hour PG at the time of remission is a better predictor of hyperglycemia relapse than traditional glycemic markers among obese Black patients presenting with DKA/SH. Testing 1-h PG at insulin discontinuation identifies individuals at high risk of developing hyperglycemia relapse.

Comparative analysis of the Parent Attitudes about Childhood Vaccines (PACV) short scale and the five categories of vaccine acceptance identified by Gust et al.

BACKGROUND: There is a need to develop a standardized tool to aid in identifying, measuring and classifying the unique needs of vaccine-hesitant parents (VHPs). This will also assist in designing tailored interventions to address these needs. The Parental Attitude about Childhood Vaccines (PACV) short scale developed by Opel et al., and the Gust et al. vaccine acceptance categories have been acknowledged as potentially useful tools to measure parental vaccine hesitancy. The PACV short scale requires further validation. In our study, we evaluated how the Gust et al. vaccine acceptance categories correspond with the PACV short scale. METHODS: As part of a larger study on vaccine attitudes, using the PACV short scale and Gust et al. vaccine acceptance categories, we assessed the correlation between the two measures using Spearman correlation coefficient, and the association between the two measures using the Cochran-Mantel-Haentszel test of association. We used logistic regression modelling to compare the association between a child's up-to-date immunization status and (a) PACV short scale and (b) Gust et al. vaccine acceptance categories. RESULTS: The PACV short scale and Gust et al. vaccine acceptance categories were positively correlated (r=0.6, df=198, p<0.05), and the Cochran-Mantel-Haentszel test of association yielded a statistically significant association (p<0.05). The two scales similarly predicted children's up-to-date immunization status for all recommended childhood vaccines. CONCLUSION: The ability of the PACV short scale to identify and classify parental vaccine hesitancy is similar to classification using Gust et al. vaccine acceptance categories, and both measure linear entities. The PACV short scale is recommended for screening parents at their first pediatric visit because it is easier to administer. A clearer understanding of how to classify parental vaccine hesitancy can be used to design tailored interventions based on these classifications, to address their specific needs.