Glycemic responses to strenuous training in male professional cyclists with type 1 diabetes: a prospective observational study
Bibliographic record
Abstract
INTRODUCTION: This prospective observational study sought to establish the glycemic, physiological and dietary demands of strenuous exercise training as part of a 9-day performance camp in a professional cycling team with type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: ; glycated hemoglobin: 7%±1% (50±6 mmol/mol); maximum rate of oxygen consumption: 73±4 mL/kg/min) performed road cycle sessions (50%-90% of the anaerobic threshold, duration 1-6 hours) over 9 consecutive days. Glycemic (Dexcom G6), nutrition and physiological data were collected throughout. Glycemic data were stratified into predefined glycemic ranges and mapped alongside exercise physiology and nutritional parameters, as well as split into daytime and night-time phases for comparative analysis. Data were assessed by means of analysis of variance and paired t-tests. A p value of ≤0.05 (two-tailed) was statistically significant. RESULTS: Higher levels of antecedent hypoglycemia in the nocturnal hours were associated with greater time spent in next-day hypoglycemia overall (p=0.003) and during exercise (p=0.019). Occurrence of nocturnal hypoglycemia was associated with over three times the risk of next-day hypoglycemia (p<0.001) and a twofold risk of low glucose during cycling (p<0.001). Moreover, there was trend for a greater amount of time spent in mild hypoglycemia during the night compared with daytime hours (p=0.080). CONCLUSION: The higher prevalence of nocturnal hypoglycemia was associated with an increased risk of next-day hypoglycemia, which extended to cycle training sessions. These data highlight the potential need for additional prebed carbohydrates and/or insulin dose reduction strategies around exercise training in professional cyclists with T1D. TRIAL REGISTRATION NUMBER: DRKS00019923.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".