Aerobic fitness does not influence the biventricular response to whole body passive heat stress
Bibliographic record
Abstract
We examined biventricular function during passive heat stress in endurance trained (ET) and untrained (UT) men to evaluate whether aerobic fitness alters the volumetric response. Body temperature was elevated ~0.8°C above baseline in 20 healthy men (10 ET, 64.4 ± 3.0 ml·kg(-1)·min(-1); and 10 UT, 46.3 ± 6.2 ml·kg(-1)·min(-1)) by circulating warm water (50°C) throughout a tube-lined suit. Cardiac magnetic resonance imaging was used to measure biventricular volumes, function, filling velocities, volumetric flow rates, and left ventricular (LV) twist and circumferential strain at baseline (BL) and after 45 min of heat stress. In both groups, passive heat stress reduced biventricular end-diastolic (ET, -19.5 ± 24.0 ml; UT, -25.1 ± 23.8 ml) and end-systolic (ET, -15.9 ± 8.8 ml; UT, -17.6 ± 7.9 ml) volumes and left atrial volume (ET, -19.2 ± 11.6 ml; UT, -15.0 ± 12.7 ml) and significantly increased heart rate (ET, 29.3 ± 9.0 beats/min; UT, 31.7 ± 10.4 beats/min) and cardiac output (ET, 3.8 ± 2.2 l/min; UT, 3.2 ± 1.4 l/min) similarly, while biventricular stroke volume was unchanged. There were no between-group differences in any parameter. Heat stress increased (P < 0.05), as a percentage of baseline values, biventricular ejection fraction (ET, 3.4 ± 5.3%; UT, 4.4 ± 3.7%), annular systolic tissue velocities (ET, 32.5 ± 34.9%; UT, 44.0 ± 38.1%), and peak LV twist (ET, 51.6 ± 59.7%; UT, 59.7 ± 54.2%) and untwisting rates (ET, 45.5 ± 42.3%; UT, 51.8 ± 55.0%) similarly in both groups. Early LV diastolic tissue and blood velocities, volumetric flow rates, and strain rates (diastole) were unchanged with heat stress in both groups. The present findings indicate that aerobic fitness does not influence the biventricular response to passive heat stress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".