Intraocular Pressure Changes of Healthy Lowlanders at Different Altitude Levels: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: High altitude, characterized by hypobaric hypoxia, low temperature and intensive ultraviolet radiation, is identifiably one of the examples of scientific enquiry into aviation and space analogs. However, little is known about the ocular physiological response, especially intraocular pressure (IOP) changes at high altitude. Objectives: This study aimed to systematically review of high altitude exposure on IOP for healthy lowlanders with unoperated eyes. Methods: A comprehensive systematic literature search was conducted in the electronic databases until September 1st, 2019. A meta-analysis was performed following the preferred reporting items for systematic review and meta-analysis statement (PRISMA). We systematically searched the studies conducted over 2,000m above sea level (a.s.l) in healthy lowlanders with measurements of IOP. Meta-analyses (random effect model and heterogeneity tests), subgroup analyses (altitude, duration, type and pattern of exposure), sensitivity analysis, funnel plot, Begger’s and Egger’s test for publication bias were performed. Quality assessment was conducted using the Newcastle–Ottawa scale. The meta-analysis was registered in the PROSPERO database (CRD42019136865). Results: Of 9595 publications searched, 20 publications (n=745) qualified for inclusion, with non-significant decrease in overall IOP (standardized mean difference (SMD): 0.14, 95% CI: -0.12 - 0.40; p=0.30) with high heterogeneity (p<0.001, I2=82%). However, subgroup analyses revealed significant decrease of IOP at high altitude of 3,000-5,500m a.s.l (SMD: 0.57, 95% CI: 0.07 - 1.06; p=0.03) whereas increase of IOP at extreme altitude of over 5,500m a.s.l (SMD: -0.34, 95% CI: -0.61 - 0.06; p=0.02). And the duration of exposure more than 72 hours (h) was likely to induce a decrease of IOP bordering on statistical significance at the 5% level (SMD: 1.29, 95% CI: 0.02 - 2.56; p=0.05). Simultaneously, we also observed significant decrease of IOP for active exposure (e.g. physical activity and hiking, SMD: 0.81, 95% CI: 0.05 - 1.57; p=0.04). Conclusion: Our analysis shows exposure to the altitude over 3,500m a.s.l, duration of exposure more than 72h and active exposure pattern may have modest, but significant effects on IOP. The higher altitude, the duration of exposure as well as physical activity seem to play crucial roles in the effects of high-altitude exposure on IOP.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".