OBJECTIVE: To compare the time in range (TIR) obtained from self-monitoring of blood glucose (SMBG) with that obtained from continuous glucose monitoring (CGM), and explore the relationship of TIR with microalbuminuria outcome, HOMA-IR and HOMA-β test.
METHODS: We recruited 400 patients with type 2 diabetes to carry out blood glucose monitoring by both SMBG and CGM for 3 consecutive days. TIR, TAR, TBR and other blood glucose variation indices were calculated respectively through the glucose data achieved from SMBG and CGM. The HOMA-IR and HOMA-β test was evaluated by an oral glucose tolerance test. Urinary microalbumin-to-creatinine ratio completed in the laboratory.
RESULTS: The median (25 %, 75 % quartile) of TIRCGM and TIRSMBG were 74.94(44.90, 88.04) and 70.83(46.88, 87.50) respectively, and there was no significant difference, p = 0.489; For every 1 % increase in TIRCGM, the risk of microalbuminuria decreased by 1.6 % (95%CI:0.973, 0.995, p = 0.006) and for every 1 % increase in TIRSMBG, the risk of microalbuminuria decreased by 1.3 % (95%CI:0.975, 0.999, p = 0.033). Stepwise multiple linear regression analysis showed an independent positive correlation between TIR (including TIRCGM and TIRSBMG) and LnDI30 and LnDI120 levels (p = 0.000).
CONCLUSIONS: The TIR calculated by SMBG was highly consistent with that reported by CGM and was significantly associated with the risk of microalbuminuria and the HOMA-β. Higher TIR quartiles were associated with lower incidence of microalbuminuria as well as higher lever of HOMA-β. For patients with limited CGM application, SMBG-derived TIR may be an alternative to CGM-derived TIR, to assess blood glucose control.

OBJECTIVE: Continuous glucose monitoring (CGM) systems are standard of care for youth with type 1 diabetes with the goal of spending >70% time in range (TIR; 70-180 mg/dL, 3.9-10 mmol/L). We aimed to understand paediatric CGM user experiences with TIR metrics considering recent discussion of shifting to time in tight range (TITR; >50% time between 70 and 140 mg/dL, 3.9 and 7.8 mmol/L).
METHODS: Semi-structured interviews and focus groups with adolescents with type 1 diabetes and parents of youth with type 1 diabetes focused on experiences with TIR goals and reactions to TITR. Groups and interviews were audio-recorded, transcribed and analysed using content analysis.
RESULTS: Thirty participants (N = 19 parents: age 43.6 ± 5.3 years, 79% female, 47% non-Hispanic White, 20 ± 5 months since child\'s diagnosis; N = 11 adolescents: age 15.3 ± 2 years, 55% female, 55% non-Hispanic White, 16 ± 3 months since diagnosis) attended. Participants had varying levels of understanding of TIR. Some developed personally preferred glucose ranges. Parents often aimed to surpass 70% TIR. Many described feelings of stress and disappointment when they did not meet a TIR goal. Concerns about TITR included increased stress and burden; risk of hypoglycaemia; and family conflict. Some participants said TITR would not change their daily lives; others said it would improve their diabetes management. Families requested care team support and a clear scientific rationale for TITR.
CONCLUSIONS: The wealth of CGM data creates frequent opportunities for assessing diabetes management and carries implications for management burden. Input from people with type 1 diabetes and their families will be critical in considering a shift in glycaemic goals and targets.

OBJECTIVE: This study aimed to assess the correlation between glycated hemoglobin A1 (HbA1c), time in range (TIR), and glycemic management indicator (GMI) in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) who were using a flash glucose monitoring (FGM) device (FreeStyle Libre; Abbott Diabetic Care, Witney, UK).
METHODS: This was a retrospective study that looked at T1D and T2D FreeStyle Libre users\' LibreView database in the period between January 2020 to June 2022. The study was conducted at the diabetes department at the King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia, following Institutional Review Board (IRB) approval. Data were collected from the LibreView website, as well as from the electronic privacy information center (EPIC) hospital records.
RESULTS: Data were available for 327 patients, mean age of 33.08(±17.1) years old, and 55.7% were females. HbA1c had a statistically significant correlation with both TIR and GMI with coefficient of correlation (r) values of 0.78 (p<0.001) and 0.82 (p<0.001), respectively. A linear regression model between TIR and Hb1Ac was also developed and found to be statistically significant (p<0.001) with an acceptable R2 value (0.60).
CONCLUSIONS: Study findings revealed that the %TIR could be a reliable predictor of Hb1Ac. Thus, Freestyle Libre was able to determine Hb1Ac as close to the lab results as possible. Therefore, it is necessary to encourage diabetes patients to achieve at least 70% TIR in order to keep Hb1Ac within the desired range.

UNASSIGNED: It is challenging for pregnant women with type 1 diabetes to maintain optimum glucose level to attain good neonatal outcomes. This study evaluated the efficacy of sensor-augmented insulin pump (SAP) with a predictive low-glucose suspend (PLGS) system in pregnant Japanese women with type 1 diabetes.
UNASSIGNED: SAP with PLGS was used in 11 of the 22 women with type 1 diabetes who delivered between 2011 and 2021 at the two medical institutions in Japan. Glucose management, insulin delivery suspension time (IST) and neonatal outcomes were retrospectively studied.
UNASSIGNED: In SAP with PLGS cases (n = 11), average glycated hemoglobin levels were < 6.5% throughout the pregnancy, and the time in range (TIR, 63-140 mg/dl) was > 70% in the second and third trimesters. PLGS was safely used without inducing ketoacidosis. Positive correlation was observed between IST and TIR (r = 0.62, p < 0.01). Negative correlation was observed between IST and time below range (TBR) (r =  - 0.40, p = 0.02), and IST and time above range (TAR) (r =  - 0.45, p = 0.01). Total daily insulin dose was adequately increased without increasing hypoglycemia. There was only one heavy-for-date HFD) infant among the 11 newborns in SAP with PLGS cases. In cases without SAP (n = 11), target glycemic levels were difficult to achieve and there were 5 HFD infants among the 11 newborns.
UNASSIGNED: SAP with PLGS was safely and effectively used in pregnant women with type 1 diabetes to achieve target glucose levels without increasing the risk of hypoglycemia, which may have led to good neonatal outcomes.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13340-024-00716-7.

BACKGROUND: Continuous glucose monitoring (CGM) devices allow for 24-h real-time measurement of interstitial glucose levels and have changed the interaction between people with diabetes and their health care providers. The large amount of data generated by CGM can be analyzed and evaluated using a set of standardized parameters, collectively named glucometrics. This review aims to provide a summary of the existing evidence on the use of glucometrics data and its impact on clinical practice based on published studies involving adults and children with type 1 diabetes (T1D) in Spain.
METHODS: The PubMed and MEDES (Spanish Medical literature) databases were searched covering the years 2018-2022 and including clinical and observational studies, consensus guidelines, and meta-analyses on CGM and glucometrics conducted in Spain.
RESULTS: A total of 16 observational studies were found on the use of CGM in Spain, which have shown that cases of severe hypoglycemia in children with T1D were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Real-world data from Spain shows that CGM is associated with improved glycemic markers (increased time in range, reduced time below and above range, and glycemic variability), and that there is a relationship between glycemic variability and hypoglycemia. Also, CGM and analysis of glucometrics proved highly useful during the COVID-19 pandemic. New glucometrics, such as the glycemic risk index, or new mathematical approaches to the analysis of CGM-derived glucose data, such as \"glucodensities,\" could help patients to achieve better glycemic control in the future.
CONCLUSIONS: By using glucometrics in clinical practice, clinicians can better assess glycemic control and a patient\'s individual response to treatment.
Continuous glucose monitoring (CGM) devices are used to monitor glucose levels in real time over 24 h. This has changed the way people with diabetes and their health care providers interact. These devices produce a large amount of data that can be analyzed and evaluated using standardized parameters called glucometrics, which include the time a patient’s glucose is in range, below range, and above range, and how much it varies over 24 h. Clinicians can use these data to better assess glycemic control and a patient\'s individual response to treatment. In this article, we summarize evidence from published studies involving adults and children with type 1 diabetes in Spain to look at how the use of these data has affected clinical practice. Studies have shown that cases of severe low blood glucose in children with diabetes were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Data from clinical practice in Spain show that CGM is associated with improved blood glucose markers. Many studies analyzed these data during the COVID-19 pandemic and showed that CGM and analysis of glucometrics were highly useful during this time. New glucometrics and approaches to the analysis of data from CGM could help patients achieve better blood glucose control.

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The introduction of closed-loop systems in the pediatric population has been a revolution in the management and evolution of diabetes. However, there are not many published studies in situations in which the feeding, schedules, and activities of the children deviate from the routine for which the systems were programmed, as in the case of a summer camp for children and adolescents with diabetes, where the specific programming of this device is not well known. It was a single-center prospective preliminary study. A total of twenty-seven patients (mean age 11.9 ± 1.9 years, 40% male, duration of diabetes 6.44 ± 2.83 years) were included (twenty with Medtronic MiniMed 780G system and seven with Tandem Control-IQ). Glucometric variables and pump functionality were monitored during the 7-day camp and in the following 3 weeks. There was no decrease from the objective TIR 70% at any moment. The worst results in Time Below Range were at 72 h from starting the camp, and the worst results in Time Above Range were in the first 24 h, with a progressive improvement after that. No episodes of level 3 hypoglycemia or ketoacidosis occurred. The use of specific programming in two integrated systems, with complex blood glucose regulation algorithms and not-prepared-for situations with increased levels of physical activity or abrupt changes in feeding routines, did not result in an increased risk of level 3 hypoglycemia and ketoacidosis for our pediatric type 1 diabetes (T1D) patients, regardless of the closed-loop device.

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OBJECTIVE: Type 1 diabetes mellitus (T1DM) is characterised by insulin deficiency. Due to perceived physical activity (PA)-related hypoglycaemia, a minority of people with T1DM exercise regularly. However, the relationship between T1DM and PA remains poorly understood. Our aim was to summarise the existing literature on the effects of PA on short-term glucose control (glycated haemoglobin or time in range) in people with T1DM.
METHODS: We searched seven electronic databases (PubMed, Embase, Cochrane library, Cinahl, SPORTDiscus, PEDro and Web Of Science) and two sources of the grey literature (ClinicalTrials.gov and ICTRP). All reviews were screened via title/abstract and full text by two independent reviewers (LE and HT), conflicts were solved by a third independent reviewer (DDC). We excluded animal studies, case reports, non-English articles, qualitative studies, conference abstracts and articles without full-text access. A meta-analysis using random effects model was performed to study the effect of PA on haemoglobin A1c (HbA1c) levels in people with T1DM.
RESULTS: We obtained 19,201 unique references across nine different electronic databases. After screening and snowballing, 68 articles were found investigating the effect of PA on glycaemic control in people with T1DM. Overall, HbA1c levels in the PA group (mean difference = 0.29% (0.20%-0.39%)), were lower compared with the control group.
CONCLUSIONS: An overall small beneficial effect of PA on glycaemic control in people with T1DM was found. Caution is advised when interpreting the results of this meta-analysis, given variations in study type, duration, frequency and intensity of physical activity across included studies.