Clinical features distinguishing angle closure from pseudoplateau versus plateau iris
Bibliographic record
Abstract
PURPOSE: To evaluate clinical aspects of patients with the diagnosis of plateau iris (PI) or pseudoplateau iris (PPI) made by ultrasound biomicroscopy (UBM) in order to determine if there are any clinical factors that can help differentiate between these two entities. METHOD: A retrospective cohort of consecutive UBM patients with the diagnosis of PI or PPI. The diagnosis of PI was based on an anteriorly positioned ciliary body that abutted the peripheral iris, a narrow (<10 degrees) or closed angle for at least 180 degrees, and the anterior portion of the iris positioned anterior to scleral spur. The diagnosis of PPI was similar to plateau except that large or a cluster of small cysts had to be present in the iridociliary sulcus. RESULTS: There were a total of 76 patients (29% male), 21 with PPI and 55 with PI. Patients with PPI were more likely to be male (p = 0.005), slightly younger (51.5 (SD 10.7) vs 57.9 (10.2) p = 0.0190), have a "bumpy" peripheral iris appearance (p = 0.003), have greater trabecular meshwork pigmentation (2.0 (0.7) vs 1.3 (0.6) p = 0.004) and have fewer clock hours of gonioscopic angle closure versus plateau iris patients (5.1 (4.3) vs 9.2 (4.2) p = 0.0009). Spherical equivalent was not significantly different between groups (0.50D (1.69) PPI vs 1.33D (2.42) PI; p = 0.187). CONCLUSIONS: In patients being referred to a UBM clinic for evaluation of angle-closure mechanism, younger males with a bumpy peripheral iris have a higher likelihood of having a diagnosis of pseudoplateau iris. However, clinical factors do not appear to discriminate well between PPI and PI. UBM is extremely helpful in confirming underlying mechanism and guiding therapy.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".