Intraocular Pressure Reduction Is Associated with Reduced Venous Pulsation Pressure
Bibliographic record
Abstract
PURPOSE: To explore whether alterations in intraocular pressure (IOP) affect vein pulsation properties using ophthalmodynamometric measures of vein pulsation pressure. PATIENTS AND METHODS: Glaucoma patients had two retinal vein pulsation pressure (VPP) measurements from upper and lower hemiveins performed by ophthalmodynamometry at least 3 months apart. All subjects had VPP and IOP recorded at two visits, with standard automated perimetry, central corneal thickness (CCT) recorded at the initial visit. Where venous pulsation was spontaneous ophthalmodynamometry could not be performed and VPP was considered equal to IOP. Change in VPP was calculated and binarized with reduction in pressure scored 1 and no change or increase scored as 0. Data analysis used a mixed logistic regression model with change in VPP as response variable and change in IOP, visual field loss (mean deviation), CCT and time interval as explanatory variables. RESULTS: 31 subjects (20 females) with mean age 60 years (sd 11) were examined with change in VPP being significantly associated with change in IOP (odds ratio 1.6/mmHg, 95% CI 1.2 to 2.1 in the glaucoma patients but not suspect patients (p = 0.0005). CONCLUSION: Change in VPP is strongly associated with change in IOP such that a reduced intraocular pressure is associated with a subsequent reduction in VPP. This indicates that reduced IOP alters some retinal vein properties however the nature and time course of these changes is not known.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".