Dose Response of Inhaled Salbutamol on Exercise Performance and Urine Concentrations
Bibliographic record
Abstract
PURPOSE: This study determined the dose-response effects of inhaled salbutamol (SAL) on time-trial performance and urine concentrations of SAL (cSAL). METHODS: Nonasthmatic, trained male cyclists and triathletes (N = 37) were studied. Day 1 consisted of screening for airway hyperresponsiveness, using a eucapnic voluntary hyperpnea test (EVH), followed by an incremental exercise test to determine V O 2max and peak power (P max). On days 2-5, athletes performed a 20-km time trial 15 min after inhalation (PI) of placebo, 200 microg (D2), 400 microg (D4), or 800 microg (D8) of SAL. At 60 min PI, urine samples were provided. All conditions were randomized and double blinded, with repeated-measures ANOVA used to determine effects of dose. Post hoc analysis was done with Tukey's HSD test. RESULTS: Seven subjects had positive responses to the EVH test, resulting in a 19% incidence within this sample; they were excluded from further participation in this study. The remaining subjects (N = 30) had a V O 2max of 67.1 (4.3) mL x kg(-1) x min(-1) and Pmax of 457 (31) W (W). There was no effect of dose on completion time (P > 0.05), mean power (P > 0.05), or mean heart rate (P > 0.05). Similarly, SAL had no effect on any metabolic or ventilatory parameters (P > 0.05). Urine cSAL increased with dose and was highly variable, with the peak value observed being 831 ng x mL(-1) after a dose of 800 microg. Moderate but significant correlations were noted between cSAL and urine specific gravity at higher doses (D4, r = 0.42; D8, r = 0.37). CONCLUSIONS: These findings suggest that inhaled SAL does not enhance time-trial performance, regardless of dose, and that urine cSAL after exercise is related to dose, demonstrates high variability, and is partially related to hydration status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".