Type 1 Diabetes and the Menstrual Cycle: Where/How Does Exercise Fit in?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".