Fluid Intake Habits in Type 1 Diabetes Individuals during Typical Training Bouts
Bibliographic record
Abstract
BACKGROUND/AIMS: Hyperglycemia may influence the hydration status in diabetic individuals. During exercise, type 1 diabetes mellitus (T1DM) individuals may be challenged by a higher risk of dehydration due to a combination of fluid losses from sweat and increased urine output via glycosuria. So far, no study has characterised spontaneous fluid intake in T1DM individuals during active trainings. METHODS: A validated questionnaire was used to assess T1DM participants' diabetes therapy, sports characteristics and fluid intake during training; results were then compared to an age- and sport-matched sample of non-diabetic individuals. RESULTS: Ninety individuals completed the survey (n = 45 T1DM individuals, n = 45 matched controls). A proportion of T1DM -individuals reported blood glucose levels greater than 10.0 mmol at both the start (28.9%) and end (24.4%) of the exercise. The mean self-reported fluid intake was greater in T1DM (0.60 ± 0.47 L·h-1) compared to that of the control (0.37 ± 0.28 L·h-1, p < 0.05). In spite of drinking fluid volumes in line with international guidelines, 84.4% of those with T1DM reported that they were still feeling thirsty at the end of their training session. CONCLUSIONS: T1DM individuals self-report spontaneously consuming fluid adequate volumes suggested by sport nutrition guidelines for non-diabetic athletes. Discrepancies in the T1DM subjectively reported feelings of thirst suggest that more education on hydration during exercise is needed for this population to adequately compensate for elevated blood glucose levels. It remains to be established whether fluid volumes suggested for healthy athletes are adequate for maintaining euhydration in T1DM patients due to their altered diuresis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".