The Athlete with Type 1 Diabetes: Transition from Case Reports to General Therapy Recommendations
Bibliographic record
Abstract
Jane E Yardley1–4 1Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, Canada; 2Alberta Diabetes Institute, Edmonton, Canada; 3Augustana Faculty, University of Alberta, Camrose, Canada; 4Women’s and Children’s Research Institute, Edmonton, CanadaCorrespondence: Jane E YardleyAugustana Faculty, University of Alberta, 4901 – 46th Avenue, Camrose, AB T4V 2R3, CanadaTel +1 780 679 1688Fax +1 780 679 1590Email jane.yardley@ualberta.caAbstract: Fear of hypoglycemia is a common barrier to exercise and physical activity for individuals with type 1 diabetes. While some of the earliest studies in this area involved only one or two participants, the link between exercise, exogenous insulin, and hypoglycemia was already clear, with the only suggested management strategies being to decrease insulin dosage and/or consume carbohydrates before and after exercise. Over the past 50 years, a great deal of knowledge has been developed around the impact of different types and intensities of exercise on blood glucose levels in this population. Recent decades have also seen the development of technologies such as continuous glucose monitors, faster-acting insulins and commercially available insulin pumps to allow for the real-time observation of interstitial glucose levels, and more precise adjustments to insulin dosage before, during and after activity. As such, there are now evidence-based exercise and physical activity guidelines for individuals with type 1 diabetes. While the risk of hypoglycemia has not been completely eliminated, therapy recommendations have evolved considerably. This review discusses the evolution of the knowledge and the technology related to type 1 diabetes and exercise that have allowed this evolution to take place.Keywords: exercise, physical activity, blood glucose, insulin, carbohydrate, continuous glucose monitoring
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".