Background: Good metabolic control of Type 1 diabetes (T1D) leads to a reduction in complications. The only validated parameter for establishing the degree of control is glycated hemoglobin (HbA1c). We examined the relationship between HbA1c and a continuous glucose monitoring (CGM) system. Materials and methods: A cohort prospective study with 191 pediatric patients with T1D was conducted. Time in range (TIR), time below range (TBR), coefficient of variation (CV), number of capillary blood glucose tests, and HbA1c before sensor insertion and at one year of use were collected. Results: Patients were classified into five groups according to HbA1c at one year of using CGM. They performed fewer capillary blood glucose test at one year using CGM (−6 +/− 2, p < 0.0001). We found statistically significant differences in TIR between categories. Although groups with HbA1c < 6.5% and HbA1c 6.5–7% had the highest TIR (62.214 and 50.462%), their values were highly below optimal control according to CGM consensus. Groups with TBR < 5% were those with HbA1c between 6.5% and 8%. Conclusions: In our study, groups classified as well-controlled by guidelines were not consistent with good control according to the CGM consensus criteria. HbA1c should not be considered as the only parameter for metabolic control. CGM parameters allow individualized targets.

Introduction: In healthcare centers with limited resources, or for patients who prefer to make continuous changes in their treatment themselves and do not want to rely solely on technology, intermittent glucose monitoring (isCGM) with an insulin pump is a viable option that warrants further study. Material and methods: prospective single-center study that collected data at 3 months and after isCGM implantation in pediatric patients with Type 1 diabetes, categorized according to their insulin regimen. Results: We found statistically significant differences in the time in range (TIR) between 70 and 180 mg/dl at 3 months after using the sensor (p = 0.017), although these differences were not maintained at 1 year (p = 0.064). When stricter TIRs (70–140 mg/dl) were analyzed, statistically significant differences were observed at 3 months (p = 0.01) and at 1 year (p = 0.018) in favor of patients using CSII. While 75% of the patients in the CSII group had good control with HbA1c < 7% after one year of sensor use, only 34.6% in the MDI group achieved these values. However, the CSII group presented a higher coefficient of variation (62.31% at 3 months and 43.08% at 1 year) (p = 0.02), and a higher number of hypoglycemic episodes (7.38% and 7.32%, respectively) (p = 0.016). The CSII group also had a higher number of capillary blood glucose measurements at the beginning of the study (8.32/day) (p = 0.249), but this number became similar between both groups after one year. Conclusions: We found statistically significant differences in favor of CSII over MDI in terms of metabolic control after one year of isCGM use. However, the TIR values were still below the range considered to be indicative of good control. These findings lead us to question whether CSII should be initially considered in specific cases where HCL is not possible, or if it would be more effective to wait until the patient is ready, or the necessary resources are available to start directly CSII integrated in a closed loop system.