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AIMS: To address the scarcity of continued education for insulin pump users, we developed and evaluated a new program (NP) for individuals transitioning to a different insulin pump. METHODS: In a randomized, controlled 3-month study, adults with type 1 diabetes and suboptimal HbA1c received either NP or usual care program (UC). The NP was designed in collaboration with representatives of the target group and incorporated technical training, case-based learning, and peer experience sharing - encompassing two group sessions, and two follow-up telephone calls. The UC included a single training session led by the pump company with hotline assistance (clinic) but no structured follow-up. The primary endpoint was the difference in time in range (TIR) (70-180 mg/dL (3.9-10.0 mmol/L)), measured by continuous glucose monitoring from baseline to 3 months post-course. Psychosocial self-efficacy was measured by the Diabetes Empowerment Scale (DES-SF). RESULTS: Thirty-nine participants (median age 43, 74% female) were included. Mean TIR increased significantly in the NP group and remained unchanged in the UC group (between-group difference in change was 13.5% [95% CI: 4.0 to 22.9], p = 0.0064). Psychosocial self-efficacy improved and HbA1c decreased only significantly in the NP group. CONCLUSIONS: Applying a novel education program at pump transition significantly improved glycemic outcomes and self-efficacy.
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Background: For people with type 1 diabetes (T1D), ensuring fast and effective recovery from hypoglycemia while avoiding posthypoglycemic hyperglycemia (rebound hyperglycemia, RH) can be challenging. The objective of this study was to investigate the frequency of RH across different treatment modalities and its impact on glycemic control. Methods: This cross-sectional real-world study included adults with T1D using continuous glucose monitoring and attending the outpatient clinic at Steno Diabetes Center Copenhagen. RH was defined as ≥1 sensor glucose value (SG) >10.0 mmol/L (180 mg/dL) starting within 2 h of an antecedent SG <3.9 mmol/L (70 mg/dL). The severity of the RH events was calculated as area under the curve (AUC) and separately for users of multiple daily injections (MDIs), unintegrated insulin pumps, sensor augmented pumps (SAPs), and automated insulin delivery (AID), respectively. Results: Across the four groups, SAP and AID users had the highest incidence of RH (2.06 ± 1.65 and 2.08 ± 1.49 events per week, respectively) and a similar percentage of hypoglycemic events leading to RH events (41.3 ± 22.8% and 39.6 ± 20.1%, respectively). The AID users with RH events were significantly shorter compared with MDI users (122 ± 72 vs. 185 ± 135 min; P < 0.0001). Overall, severity of RH was inversely associated with more advanced technology (P < 0.001) and inversely associated (P < 0.001) with time in target range (TIR). Conclusions: Groups with insulin suspension features experienced the highest frequency of RH; however, AID users tended to experience shorter and less severe RH events. The association between the severity of RH events and TIR suggests that RH should be assessed and used in the guidance of hypoglycemia management.
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Continuous glucose monitors (CGMs) are valuable tools for improving glycemic control, yet their accuracy might be influenced by physical activity. This study sought to assess the accuracy of the three latest factory-calibrated CGM systems available in Europe at the time the study was conducted, both during aerobic exercise and in typical daily scenarios. The accuracy evaluation, based on metrics such as the median absolute relative difference (MARD) and point and rate error-grid analyses (PEGA and REGA), involved 13 adults with type 1 diabetes. Participants wore all sensors during a 1 h in-clinic exercise session followed by a subsequent 3-day home period, with blood glucose measurements serving as reference values in both contexts. During exercise, no statistically significant differences in MARD were observed (Dexcom G6: 12.6%, Guardian 4: 10.7%, and Freestyle Libre 2: 17.2%; p = 0.31), and similarly, no significant differences emerged in PEGA-zone-AB (100%, 100%, 96.8%; p = 0.37). Nevertheless, Freestyle Libre 2 showed comparatively diminished accuracy in estimating glucose trends during exercise (REGA-zone-AB: 100%, 93.0%, 73.3%; p = 0.0003). In the home environment, Freestyle Libre 2 exhibited a significantly higher MARD when compared to the other systems (10.2%, 11.9%, 16.7%, p = 0.02). Overall, Dexcom G6 and Guardian 4 demonstrated superior accuracy in both exercise and daily life scenarios compared to Freestyle Libre 2.