The Impact of Acetazolamide and Methazolamide on Exercise Performance in Normoxia and Hypoxia
Bibliographic record
Abstract
Doherty, Connor J., Jou-Chung Chang, Benjamin P. Thompson, Erik R. Swenson, Glen E. Foster, and Paolo B. Dominelli. The impact of acetazolamide and methazolamide on exercise performance in normoxia and hypoxia. High Alt Med Biol . 24:7–18, 2023.—Carbonic anhydrase (CA) inhibitors are commonly prescribed for acute mountain sickness (AMS). In this review, we sought to examine how two CA inhibitors, acetazolamide (AZ) and methazolamide (MZ), affect exercise performance in normoxia and hypoxia. First, we briefly describe the role of CA inhibition in facilitating the increase in ventilation and arterial oxygenation in preventing and treating AMS. Next, we detail how AZ affects exercise performance in normoxia and hypoxia and this is followed by a discussion on MZ. We emphasize that the overarching focus of the review is how the two drugs potentially affect exercise performance, rather than their ability to prevent/treat AMS per se , their interrelationship will be discussed. Overall, we suggest that AZ hinders exercise performance in normoxia, but may be beneficial in hypoxia. Based upon head-to-head studies of AZ and MZ in humans on diaphragmatic and locomotor strength in normoxia, MZ may be a better CA inhibitor when exercise performance is crucial at high altitude.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".