Visual Field Loss Morphology in High- and Normal-Tension Glaucoma
Bibliographic record
Abstract
Purpose. To determine whether the patterns of visual field damage between high-tension glaucoma (HTG) and normal-tension glaucoma (NTG) are equivalent. Methods. In this retrospective cross-sectional study, fifty-one NTG and 57 HTG patients were recruited. For each recruited patient only the left eye was chosen. Glaucomatous patients had abnormal visual fields and/or glaucomatous changes at the optic nerve head. They were classified as HTG or NTG on the basis of intraocular pressure (IOP) measurements. Patients' visual fields were analyzed by using Humphrey Field Analyzer (HFA), program 30-2, full threshold. The visual field sensitivity values and the pattern deviation map values of the 72 tested points were considered. Then a pointwise analysis and an area analysis, based on the Glaucoma Hemifield test criteria, were performed, and a comparison between the two subgroups was made by Student's t test. Results. Between NTG and HTG, no significant difference was found pointwise for almost all the visual field points, except for two locations. One was under the blind spot, and the other was in the inferior hemifield around the twenty-degree position. When area analysis was considered, three areas showed a significantly different sensitivity between HTG and NTG. Conclusions. These data suggested that there was no relevant difference in the pointwise analysis between NTG and HTG; however, when visual field areas were compared, no difference in paracentral areas was found between NTG and HTG, but superior nasal step and inferior and superior scotomata showed to be deeper in HTG than in NTG.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".