AB080. Exercise induced changes in intraocular pressure is related to systemic dehydration
Bibliographic record
Abstract
Background: A transient reduction in intraocular pressure (IOP) after an aerobic exercise is found time and again across studies in literature. It has been suggested that systemic dehydration could be a possible mechanism driving these hypotensive effects of exercise. However, IOP reduction never had been examine in hyper versus hypo-hydration conditions for a same group of participants. The purpose of this study is to examine the influence of hyper and hypo hydration conditions on exercise-induced fluctuations in intraocular pressure. Methods: Thirteen participants rode an ergocycle in a temperate room for 90 minutes, at 59% of their maximal aerobic capacity, in a state of both hyper and hypo-hydration. IOP was measured at 0, 5, 30, 60 and 90 minutes, and 30 minutes after exercise. Reduction in body weight was measured at 0, 30, 60 and 90 minutes. Results: There is an initial drop in IOP under both conditions followed by a rise in IOP at 30 minutes that is nearly equal to the baseline. From that point on, IOP hovers around baseline values in the hypo-hydrated condition and increases until the end of the exercise protocol in the hyper-hydrated condition. A repeated-measures ANOVA showed a significant interaction between time and condition F(5,60) =3.99, P=0.003, as well as a main effect of time F(5,60) =7.90, P<0.001, and a main effect of condition F(1,12) =5.83, P=0.033. Conclusions: The results of this study, when taken with others that looked specifically at factors of exercise, hydration and IOP suggest that fluctuations in IOP during exercise are likely a homeostatic response related fluid intake and not because of any specific benefit incurred through exercise.
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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) | 0.006 | 0.001 |
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".