Hot flushes, vascular reactivity and the role of the α-adrenergic system
Bibliographic record
Abstract
ABSTRACT Background Seventy percent of postmenopausal women suffer from hot flushes but the pathophysiology is poorly understood. Proposed mechanisms include altered peripheral vascular reactivity and a narrowed thermoneutral zone. A trigger has not yet been identified; however, the α-adrenergic system, and specifically noradrenaline, has been implicated. Aim To assess the role of the α-adrenergic system by studying the effect of clonidine (α-adrenergic agonist) on flushes and cutaneous microvascular perfusion. Methods Thirty-two postmenopausal women with severe flushing and 14 non-flushing postmenopausal women were recruited. Cutaneous microvascular perfusion was measured using laser Doppler imaging and endothelial function was assessed by iontophoresis (administration of vasoactive agents through the skin by an electric current) of acetylcholine (ACh - endothelium-dependent) and sodium nitroprusside (SNP - endothelium-independent). In a double-blind, longitudinal, cross-over study, clonidine (an α-adrenergic agonist) was compared to placebo in its ability to modulate this response in the flushing group of women. Results The response of the subcutaneous vessels was greater in women who flushed than those who did not (ACh, p < 0.001 and SNP, p = 0.001). However, even though the intensity and number of flushes were decreased by clonidine, there was no difference compared to placebo (p = 0.21) and this 'placebo effect' was also noted in perfusion responses (ACh, p = 0.98; SNP, p = 0.50). Conclusion There was a significant 'placebo effect' for both clinical response and the reactivity of the subcutaneous vessels, making conclusions regarding the role of the α-adrenergic nervous system in hot flushing difficult to determine at a peripheral level. The mechanism for the change in vascular reactivity remains unclear.
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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".