Whole-Body Heat Loss during Exercise in the Heat Is Not Impaired in Type 1 Diabetes
Bibliographic record
Abstract
PURPOSE: The objective of this study is to determine whether individuals with type 1 diabetes exhibit impairments in local and whole-body heat loss responses that could affect core temperature regulation during exercise in the heat compared with matched, nondiabetic individuals. METHODS: Twelve otherwise healthy individuals with type 1 diabetes (HbA1c = 7.7% ± 0.3%) and 12 controls matched for age, sex, body surface area, and physical fitness cycled continuously for 60 min at a set rate of metabolic heat production (approximately 400 W) in a whole-body direct calorimeter (35°C and 20% relative humidity). Local sweat rate (ventilated capsule) was measured on the back and skin blood flow (laser Doppler velocimetry) on the forearm. Core (rectal and esophageal) and mean skin temperatures and heart rate were measured continuously. Whole-body heat exchange and change in body heat content were measured using simultaneous direct whole-body and indirect calorimetry. RESULTS: The change (mean ± SE) in body heat content was similar between groups during exercise (diabetes, 409 ± 27 kJ; control, 386 ± 33 kJ; P = 0.584) and recovery (diabetes, -115 ± 16 kJ; control, -93 ± 24 kJ; P = 0.457). Local heat loss responses of sweating (P = 0.783) and skin blood flow (P = 0.078) as well as rectal temperature (diabetes, 37.87°C ± 0.10°C; control, 37.85°C; ± 0.13°C; P = 0.977) and heart rate (diabetes, 130 ± 9 beats·min, vs control, 126 ± 8 beats·min, P = 0.326) were comparable at the end of the exercise period. CONCLUSION: During light-to-moderate-intensity exercise performed under conditions permitting full sweat evaporation, otherwise healthy type 1 diabetic individuals did not show impaired heat loss responses during heat exposure when compared with matched individuals without diabetes.
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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 | 0.000 |
| 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".