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INTRODUCTION: 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. CONCLUSION: 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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BACKGROUND: A study to assess the glucose levels of people with type 1 diabetes (T1D) overnight, based on the insulin type and timing. METHODS: A real-world, retrospective study of T1D, using multiple daily insulin injections. Continuous glucose monitoring and insulin injection data were collected for ten hours after dinner using the Insulclock® connected cap. Meal events were identified using the ROC detection methodology. The timing of the rapid insulin, second injections, and the type of insulin analogs used, were evaluated. RESULTS: The nocturnal profiles (n = 775, 49 subjects) were analyzed. A higher glucose AUC of over 180 mg/dL was observed in subjects with delayed injections (number; %; mg/dL × h): -45-15 min (n = 136; 17.5%, 175.9 ± 271.0); -15-0 min (n = 231; 29.8%, 164.0 ± 2 37.1); 0 + 45 min (n = 408; 52.6%, 203.6 ± 260.9), (p = 0.049). The use of ultrarapid insulin (FiAsp®) (URI) vs. rapid insulin (RI) analogs was associated with less hypoglycemia events (7.1 vs. 13.6%; p = 0.005) and TBR70 (1.7 ± 6.9 vs. 4.6 ± 13.9%; p = 0.003). Users of glargine U300 vs. degludec had a higher TIR (70.7 vs. 58.5%) (adjusted R-squared: 0.22, p < 0.001). The use of a correction injection (n = 144, 18.6%) was associated with a higher number of hypoglycemia events (18.1 vs. 9.5%; p = 0.003), TBR70 (5.5 ± 14.2 vs. 3.0 ± 11.1%; p = 0.003), a glucose AUC of over 180 mg/dL (226.1 ± 257.8 vs. 178.0 ± 255.3 mg/dL × h; p = 0.001), and a lower TIR (56.0 ± 27.4 vs. 62.7 ± 29.6 mg/dL × h; p = 0.004). CONCLUSION: The dinner rapid insulin timing, insulin type, and the use of correction injections affect the nocturnal glucose profile in T1D.
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Background: Hyperglycaemia is an early and frequent adverse event during alpelisib treatment. METALLICA aimed to evaluate prophylactic metformin to prevent or reduce hyperglycaemia occurrence in patients with HR+/HER2-/PIK3CA-mutated advanced breast cancer (ABC). Methods: Between August 13th, 2020 and March 23rd, 2022, this 2-cohort, phase 2, multicentre, single-arm trial (NCT04300790) enrolled patients with HR+/HER2-/PIK3CA-mutated ABC: cohort A, normal glycaemia (fasting plasma glucose <100 mg/dL [<5.6 mmol/L] and HbA1c <5.7%), and cohort B, prediabetes (fasting plasma glucose 100-140 mg/dL [5.6-7.8 mmol/L] and/or haemoglobin A1C [HbA1c] 5.7-6.4%). Participants were at least 18 years old, with Eastern Cooperative Oncology Group performance status of 0-1, and up to two prior lines of endocrine therapy (ET) for ABC. Alpelisib plus ET were administered in 28-day cycles after initiation of prophylactic metformin plus ET. Primary endpoint was the incidence of grade 3-4 hyperglycaemia over the first 8 weeks. Secondary endpoints included safety, progression-free survival (PFS), objective response rate (ORR), and clinical benefit rate (CBR). The primary objective for cohort A and B is met with ≤7 (14.6%) and ≤4 (20%) patients with grade 3-4 hyperglycaemia over the first 8 weeks, respectively. Findings: 233 patients were screened, and 68 (20.2%) patients were enrolled in cohorts A (n = 48) and B (n = 20). Median follow-up was 7.8 months (IQR 1.4-19.6). Over the first 8 weeks, one (2.1%) of 48 patients in cohort A (95% CI: 0.5-11.1; P < 0.0001), and three (15.0%) of 20 patients in cohort B (95% CI: 5.6-37.8; P = 0.016) had grade 3-4 hyperglycaemia. Serious treatment-related adverse events occurred in seven patients (10.3%). The most common were rash (two [2.9%]), vomiting (two [2.9%]), and diarrhoea (two [2.9%]). Discontinuation of alpelisib caused by AEs was reported in nine patients (13.2%), none caused by hyperglycaemia. At data cutoff (15 June, 2022), no treatment-related deaths were observed. In the full analysis set, median PFS was 7.3 months (95% CI: 5.9-not reached), ORR was 20.6% (95% CI: 11.7-32.1%), and CBR was 52.9% (95% CI: 40.4-65.2). Interpretation: In HR+/HER2-/PIK3CA-mutated ABC, prophylactic metformin before alpelisib plus endocrine treatment has low incidence and severity of alpelicib-induced hyperglycaemia. Funding: Novartis Pharmaceuticals.
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Aims: To evaluate the metabolic and clinical outcomes in the Spanish type 1 diabetes mellitus (T1D) population before and after COVID-19 vaccination. Methods: A retrospective observational study was carried out in Spanish public hospitals previously enrolled in the SED1 study. Adults and children with T1D were included and their clinical electronic records were reviewed. Clinical, laboratory, and glucometric parameters from continuous glucose monitoring (CGM) data corresponding to the periods before and after administering the first COVID-19 vaccination were analyzed. Results: A total of 26 centers and 228 patients participated in this new phase of the SED1 study and 187 were finally evaluable (mean age 37.5 ± 15.6 years, 56.7% women). Overall, 94.6% of the sample was vaccinated, and this percentage increased with higher levels of education (p-value = 0.027). In the pre- and post-vaccination periods, respectively, the number of patients with acute hyperglycemic decompensation was 6/161 (3.7%) and 7/161 (4.3%) (p = 1) and with acute hypoglycemic decompensation was 6/161 (3.7%) and 6/161 (3.7%) (p = 1). The HbA1c level was lower in the post-vaccination period(mean ± SD, mg/dL): pre-vaccination 7.4 ± 0.9; post-vaccination 7.2 ± 1.0, (-0.19; p-value = 0.0006). A total of 31.9% of patients (95% CI: 24.7-39.7) in the pre-vaccination period and 45.0% (IC95%: 37.1-53.1) in the post-vaccine period had HbA1c < 7% (p-value < 0.001). Glucometrics from CGM data also showed numerical improvements post-vaccination. Conclusions: The COVID-19 vaccination was highly accepted in the Spanish T1D population, with hesitancy about the COVID-19 vaccine being higher in those with lower educational levels. A mildly better glycemic control was observed in the post-vaccination period.
