Effect of Aerobic Exercise at Different Intensities on Intraocular Pressure in Young Males
Bibliographic record
Abstract
PRCIS: High intensity aerobic exercise significantly reduced intraocular pressure in healthy young male adults. OBJECTIVE: This study sought to determine how aerobic exercise at various intensities affects intraocular pressure (IOP) in young adults. DESIGN: A repeated measures design was adopted. PARTICIPANTS: A group of 20 volunteers (mean age: 21.24±1.73 y) took part in this study. METHODS: IOP was measured with a tonometer (iCare TA01i, Icare Finland, Finland). Subjects completed 4 cycle ergometer sessions. During the first session, power was increased by 60 W every 3 minutes until exhaustion, corresponding to peak power. For the 3 following tests, each lasting 25 minutes, subjects exercised at intensities of 50%, 70%, and 85% of peak power, respectively, and measurements were taken every 5 minutes. MAIN OUTCOME MEASURES: IOP, as determined using a tonometer, was the primary measure. RESULTS: There was a significant reduction ( P <0.05) in IOP of both eyes during the 25 minutes high-intensity (85%) exercise test. There were also significant interactions between exercise durations and intensities. During high-intensity exercise, IOP, blood pressure, blood lactate, and the rating of perceived exertion were significantly related ( P <0.01). CONCLUSIONS: These data show a significant reduction in IOP at high-intensity aerobic exercise, which may have implications for the management of ocular health.
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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) | 0.001 | 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".