Exercise performance increase in smokeless tobacco‐user athletes after overnight nicotine abstinence
Bibliographic record
Abstract
The use of nicotine administered through smokeless tobacco (snus) has increased among athletes. The purpose of this study was to investigate the ergogenic effects of snus on aerobic performance during exercise until exhaustion in athletes after abstinence or satiety nicotine conditions. The study utilized a randomized, controlled, within‐subject design experiment. Sixteen male snus‐user athletes completed an exercise until exhaustion at a constant load of their 80% of (calculated by a maximal incremental test) in two separate sessions, corresponding to nicotine conditions: 12‐hour overnight abstinence and satiety. A portion of 1 g of snus (~8 mg/g of nicotine) was administered 25 minutes before each experimental test. In each session, time to exhaustion (TTE), global rating of perceived exertion, cardiovascular and metabolic responses, and muscle and cerebral oxygenation were measured. Nicotine and cotinine analysis confirmed session conditions (abstinence or satiety). Snus induced a significant increase (+13.1%) of TTE following abstinence (24.1 ± 10.7 minutes) compared to satiety condition (20.9 ± 8.0 minutes; P = 0.0131). The baseline values revealed that abstinence of snus induced significant increase in the oxygenation of the muscular tissues (+4%), in metabolic values and in cardiovascular parameters, when compared to satiety condition. Our results indicate an increase of exercise performance (+13.1% TTE) due to snus administration in an abstinence condition. Considering that twelve hours of abstinence from snus‐contained nicotine affected metabolic, cardiovascular and muscular tissue oxygenation, we suggest that snus administration at test time might relieve these withdrawal changes and yield an increase in time to exhaustion.
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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".