Novel evidence on the effect of tramadol on self-paced high-intensity cycling
Bibliographic record
Abstract
The use of tramadol is a controversial current topic of debate in cycling, although little is known about its potential ergogenic effect and negative impact on attention compromising rider safety. In order to provide novel evidence on this issue, we tested 29 participants in a pre-loaded time trial (TT; a 20-min TT preceded by 40-min of constant work-rate at 60% of the VO2max) on a cycle-ergometer after ingesting 100 mg of tramadol. Placebo and paracetamol (1.5 g) -the other mild (and legal) analgesic used in cycling-, were included as control conditions (in separate days). Participants also performed the Psychomotor Vigilance Task (PVT) at rest and a Sustained Attention to Response Task (SART) during the 60 min of exercise. Oscillatory electroencephalography (EEG) activity was measured throughout the exercise. The results showed higher mean power output during the 20-min TT under tramadol than with paracetamol, but no reliable difference was reported between tramadol and placebo (nor between paracetamol and placebo). Tramadol (vs. paracetamol and placebo), resulted in faster responses in the PVT, higher heart rate during the whole exercise period, and lower ratings of perceived exertion in the 40-min constant work-rate. The main effect of substance was reliable in the SART during the 40-min constant workload, with slower reaction time, but better accuracy for tramadol and paracetamol than for placebo. No differences as a function of substance intake were reported in the SART during the 20-min TT. The analysis of EEG tonic spectral power revealed a reliable main effect of substance at rest (with larger power in the tramadol condition than in the other conditions) while no differences in EEG activity were found during the exercise. In conclusion, this study supports the increased behavioural and neural efficiency at rest for tramadol but not the proposed ergogenic or cognitive (harmful) effect of tramadol (vs. placebo) during self-paced high intensity cycling.
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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) | 0.005 | 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".