Acute Effects of Resistance Exercise on Intraocular Pressure in Healthy Adults: A Systematic Review
Bibliographic record
Abstract
ABSTRACT: Hackett, DA, Li, J, Wang, B, Way, KL, Cross, T, and Tran, DL. Acute effects of resistance exercise on intraocular pressure in healthy adults: A systematic review. J Strength Cond Res 38(2): 394-404, 2024-Intraocular pressure (IOP) tends to fluctuate during a resistance exercise (RE). This systematic review examines the acute effects of RE on IOP in healthy adults and factors that influence changes in IOP. Five electronic databases were searched using terms related to RE and IOP. A strict inclusion criterion was applied, which included being 55 years or younger with no medical conditions and RE intensity needing to be quantifiable (e.g., based on a maximal effort). Thirty-four studies met the inclusion criteria for this review. Isometric and isotonic contractions produced similar changes in IOP during RE up to 28.7 mm Hg. Exercises that involved larger muscle mass, such as squats and leg press, were found to produce changes in IOP during exercise ranging from 3.1 to 28.7 mm Hg. Smaller changes in IOP during RE were found for exercises engaging less muscle mass (e.g., handgrip and bicep curls). Intraocular pressure was found to increase during RE when lifting heavier loads and with longer exercise durations (e.g., greater repetitions). The Valsalva maneuver (VM) and breath-hold during RE accentuated the change in IOP, with more extreme changes observed with the VM. However, most studies showed that postexercise IOP returned to baseline after approximately 1 minute of recovery. An acute increase in IOP is observed during RE in healthy adults with fluctuations of varying magnitude. Factors that independently increase IOP during RE include exercises involving larger muscle mass, heavy loads, greater set duration, and when the VM or breath-hold is performed.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".