Predicting posterior capsule opacification: Value of early retroillumination imaging
Bibliographic record
Abstract
PURPOSE: To investigate the value of early retroillumination imaging of the posterior capsule in predicting the eventual development of posterior capsule opacification (PCO). SETTING: Ophthalmology Department, St. Thomas' Hospital, and Department of Physics, King's College, London, United Kingdom. METHODS: All patients with retroillumination images of the posterior capsule taken 6 months and 2 years after uneventful phacoemulsification with in-the-bag intraocular lens (IOL) implantation were selected. The images were taken using the same hardware and analyzed with the same software to calculate the percentage area of the posterior capsule covered by lens epithelial cells. The percentage area of PCO with all IOL types 6 months postoperatively was correlated with that at 2 years. RESULTS: One hundred forty patients had analyzable images at 6 months and 2 years. Of these, 63 had a poly(methyl methacrylate) (PMMA) IOL (Pharmacia 812A or Storz P497UV), 33 an acrylic (Alcon AcrySof MA30 or SA30), 22 a silicone (Allergan SI-30), and 22 a hydrophilic acrylic (Bausch & Lomb Hydroview H60). The correlation of the percentage area of PCO at 6 months with that at 2 years resulted in an r value of 0.71 (P <.0001) in the entire group. The r value was 0.48 in the PMMA group and 0.86 in the foldable IOL group (P <.0001) (r value: AcrySof, 0.66; silicone, 0.82; Hydroview, 0.75). CONCLUSIONS: Retroillumination imaging of the posterior capsule 6 months after cataract surgery predicted the PCO outcome at 2 years in eyes with foldable IOLs.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".