Compression garments do not alter cerebrovascular responses to orthostatic stress after mild passive heating
Bibliographic record
Abstract
Whole-body heating increases the likelihood of syncope, whereas utilizing lower-body compression garments may reduce syncope risk. We hypothesized that graded compression garments would reduce the typically observed large postural reductions in arterial blood pressure and middle cerebral artery velocity, in normothermia and especially once passively heat stressed. Fifteen men (age: 27 ± 4 years, aerobic fitness range: 30-75 mL/kg(/) min) completed a supine-to-stand orthostatic challenge for 3 min at normothermia and after passive heating (esophageal temperature, +0.5 °C from baseline) on two occasions (> 7 days): once wearing commercially available compression trousers and once wearing low-compression placebo trousers (randomized order). Blood flow velocity in the middle cerebral artery (transcranial Doppler), mean arterial blood pressure (mean BP: Finometer) and end-tidal carbon dioxide pressure were measured continuously. During normothermia, compression, garments did not alter the magnitude of the postural changes in mean BP or middle cerebral artery velocity. After passive heating, although the magnitudes of these changes were exaggerated, they were not significantly affected by compression garments. Compression garments did not attenuate the initial or sustained orthostatic hypotension associated with posture change, either during normothermia or following passive heat stress.
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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 | 0.000 |
| 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 | 0.000 |
| 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".