Cambios glucémicos durante el ciclo menstrual en mujeres con diabetes mellitus tipo 1

Glycemic Control Across the Menstrual Cycle in Women with Type 1 Diabetes Using the MiniMed 780G Advanced Hybrid Closed-Loop System: The 780MENS Prospective Study

Objective: To evaluate whether the MiniMed™ 780G advanced hybrid closed-loop (AHCL) system maintains similar glycemic control across two different phases of the menstrual cycle in women with type 1 diabetes (T1D) and to analyze the system's performance in these situations. Methods: Continuous glucose monitoring (CGM) and insulin delivery metrics from 12 participants with T1D using the MiniMed™ 780G AHCL were analyzed throughout 3 prospectively recorded, consecutive menstrual cycles (36 cycles in total). Mixed models were used to compare the different variables between the early follicular phase and late luteal phase. Results: A higher average glucose was found throughout the late luteal phase compared with the early follicular phase (139.5 [133.5, 145.2] vs. 131.5 [126.8, 140.2] mg/dl, respectively, P = 0.002), together with an increase in total daily insulin dose (37.2 ± 11.9 vs. 33.6 ± 12.2 IU, P < 0.001). However, similar values between phases were observed for most of the remaining CGM metrics, including time in range (83.0 [76.0, 87.5] vs. 85.0 [79.8, 89.0] %, P = 0.101). Conclusion: Our results suggest that differences in glycemic control may be found across the menstrual cycle in women with T1D using the MiniMed™ 780G AHCL. Although higher average glucose levels may be expected in the late luteal phase, the deterioration of glycemic control during this phase may be mild with the MiniMed™ 780G AHCL, given the similarities for most of the CGM metrics with respect to the early follicular phase.

Menstrual Cycle, Glucose Control and Insulin Sensitivity in Type 1 Diabetes: A Systematic Review

The correlation between the menstrual cycle and glucose control in type 1 diabetes has been the focus of several studies since the 1920s, but a few critical aspects made it particularly challenging to reach conclusive evidence. The aim of this systematic review is to reveal more solid information about the impact of the menstrual cycle on glycaemic outcomes and insulin sensitivity in type 1 diabetes and highlight the less researched areas. The literature was searched by two authors independently using PubMed/MEDLINE, Embase and Scopus (last search on 2 November 2022). The retrieved data did not allow us to perform a meta-analysis. We included 14 studies published between 1990 and 2022, with sample sizes from 4 to 124 patients. We found a wide heterogeneity in the definition of the menstrual cycle phases, glucose metrics, techniques for determining insulin sensitivity, hormonal assessment and other interfering factors considered, with an overall high risk of bias. There is no conclusive evidence, and published data do not allow us to achieve quantitative results. In a subset of patients, a possible worsening of insulin sensitivity and hyperglycaemia in the luteal phase could be observed. From the clinical standpoint, a cautious strategy based on patient-specific patterns can be considered until new, solid evidence is obtained.

Type 1 Diabetes and the Menstrual Cycle: Where/How Does Exercise Fit in?

Regular exercise is associated with substantial health benefits for individuals with type 1 diabetes (T1D). However, the fear of hypoglycemia (low blood glucose) due to activity-induced declines in blood glucose levels acts as a major barrier to partaking in exercise in this population. For females with T1D, hormonal fluctuations during the menstrual cycle and their effects on blood glucose levels can act as an additional barrier. The impact that these cyclic changes may have on blood glucose and insulin needs and the consequent risk of hypoglycemia during or after exercise are still unknown in this population. Therefore, in this narrative review, we gathered existing knowledge about the menstrual cycle in T1D and the effects of different cyclic phases on substrate metabolism and glucose response to exercise in females with T1D to increase knowledge and understanding around exercise in this underrepresented population. This increased knowledge in such an understudied area can help to better inform exercise guidelines for females with T1D. It can also play an important role in eliminating a significant barrier to exercise in this population, which has the potential to increase activity, improve mental health and quality of life, and decrease the risk of diabetes-related complications.

Ambulatory Glucose Profile According to Different Phases of the Menstrual Cycle in Women Living With Type 1 Diabetes

CONTEXT

Some women living with type 1 diabetes complain of changes in glucose values according to the different phases of menstruation.

OBJECTIVE

To evaluate this variability through continuous glucose monitoring (CGM) data in type 1 diabetes patients.

DESIGN

Observational study.

SETTING

Ambulatory data, recruitment in 2 centers in the Paris region.

PATIENTS

Twenty-four women with type 1 diabetes having spontaneous menstrual cycles.

INTERVENTION

Collection of CGM data for 62 spontaneous menstrual cycles, with evaluation of five 3-day phases during each cycle: (1) early follicular (menstruations), (2) mid-follicular, (3) peri-ovulatory, (4) mid-luteal, and (5) late luteal.

MAIN OUTCOME MEASURE

Time in range (TIR, prespecified).

RESULTS

TIR decreased for each consecutive phase (61 ± 18%; 59 ± 18%; 59 ± 20%; 57 ± 18%; and 55 ± 20%, P = 0.02). The linear mixed model highlighted a decrease in TIR in the mid-luteal (P = 0.03) and late luteal (P < 0.001) phases compared with the early follicular phase. Time above range was significantly higher during the late luteal phase than the early follicular phase (P = 0.003). Time below range was significantly higher during the mid-follicular phase than in the early follicular phase.

CONCLUSION

In most of the study population, glucose levels rose linearly throughout the menstrual cycle, reaching a maximum in the late luteal phase. A sharp decrease was seen for most participants at the beginning of menstrual bleeding. This should be taken into consideration in daily care of type 1 diabetes patients to avoid hypoglycemia.

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.