Effects of intravenous propranolol on heat pain sensitivity in healthy men
Bibliographic record
Abstract
BACKGROUND: Clinical studies have shown opioid-sparing effects of β-adrenergic antagonists perioperatively and β-blockers are being investigated for chronic musculoskeletal pain. However, the direct analgesic effects of β-blockers have rarely been examined in healthy humans. METHODS: In a randomized, counter-balanced, double-blind, within-subject crossover design, we tested the effect of the lipophilic β-blocker propranolol (0.035 mg/kg body weight i.v.) on heat pain sensitivity in 39 healthy males, compared with placebo. To test for peripheral versus central effects, the peripherally acting β-blocker sotalol was also examined. Experimental stimuli were brief superficial noxious heat stimuli applied to the volar forearm. Non-painful cold stimuli were included to test for specificity. Sedation, mood and anxiety were assessed to investigate potential mechanisms underlying any analgesic effect. β-blocker effects on blood pressure were incorporated into the analysis because of a known inverse relationship between pain sensitivity and systolic blood pressure. RESULTS: Propranolol significantly decreased perceived intensity of heat pain stimuli but only in participants with small propranolol-induced blood pressure decreases. Even in this group, the effect was small (4%). Propranolol did not influence perceived intensity of non-noxious stimuli and had no effect on sedation, anxiety or mood. Sotalol did not influence heat pain sensitivity. CONCLUSIONS: Propranolol decreased pain sensitivity but its analgesic effects were small and counteracted by blood pressure decreases. The analgesic effects were not mediated by peripheral β-receptor blockade, sedation, mood or anxiety. The small effect indicates that the utility of β-blockers for clinical pain must be related to factors that do not play a significant role for experimental pain.
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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) | 0.002 | 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".