Effect of Moderate Intraocular Pressure Changes on Topographic Measurements With Confocal Scanning Laser Tomography in Patients With Glaucoma
Bibliographic record
Abstract
OBJECTIVE: To evaluate optic disc topography changes after intraocular pressure (IOP) modulation in patients with glaucoma. METHODS: Twenty-three patients with glaucoma were studied. Three mean optic disc topography images were obtained with the Heidelberg Retina Tomograph II at baseline and weeks 1, 2, 4, and 8 (visits 1, 2, 3, 4, and 5, respectively). Topical medications were discontinued in the study eye after visit 1 and resumed after visit 4 but maintained in the contralateral control eye. Central corneal thickness was measured at the last visit. Topographic changes were determined by stereometric parameters (rim area and mean cup depth) and at discrete topographic locations using the Topographic Change Analysis program (from the Heidelberg Retina Tomograph II). RESULTS: In the study eyes, IOP increased significantly (5.4 mm Hg at visit 4; P<.001) after withdrawal of topical medications but returned to baseline levels after resuming medications; no statistically significant topographic changes, however, were observed. Moreover, no relationship between change in IOP and stereometric parameters was observed. Central corneal thickness was not associated with changes in optic disc topography induced by IOP modulation. CONCLUSION: In patients with glaucoma, significant but relatively moderate IOP increases and decreases on the order of 5 mm Hg did not appear to have an effect on optic disc topography.
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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 | 0.004 |
| 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".