Lower body muscle tensing is an effective countermeasure to initial orthostatic hypotension induced cerebral hypo‐perfusion upon standing from a squatted position
Bibliographic record
Abstract
PURPOSE to examine the effects of 5 s of lower body muscle tensing (LBMT) after rising from squat on middle cerebral artery blood velocity (MCABV) following a squat‐to‐stand protocol. METHODS Healthy subject (n =8; 24.4 ±1.9 yrs) performed a squat‐to‐stand protocol. Upon standing participants performed either no manoeuvre (Control) or LBMT which was held for 5 s. MCABV (cm/s; surrogate for cerebral perfusion) was measured with transcranial Doppler ultrasound (TCD), mean arterial pressure (MAP) via finger photoplethysmography. Cerebral blood pressure (CBP) was calculated by measuring the hydrostatic column from the heart (MAP) to the TCD probe. Cerebral vascular conductance (CVC) was calculated from MCABV and CBP. RESULTS Data are mean ±SD. The drop in MAP upon rising from squat was −15.8 ±3.9 mmHg in Control vs. −6.02 ±10.5 mmHg in LBMT, p < 0.05. This represented a 62% attenuation of hypotension via LBMT. MCABV decreased by −11.8 ±3.07 cm/s in Control vs. −3.72 ±4.48 cm/s in LBMT, P <0.05, which represents a 68% attenuation of cerebral hypo‐perfusion. CONCLUSIONS LBMT for the first 5 s upon rising from squat is an effective countermeasure for minimizing cerebral hypo‐perfusion. NSERC .
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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) | 0.002 | 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".