Pattern of posterior capsule opacification models 2 years postoperatively with 2 single-piece acrylic intraocular lenses
Bibliographic record
Abstract
PURPOSE: To compare posterior capsule opacification (PCO) in eyes with 1 of 2 models of 1-piece acrylic intraocular lenses (IOLs). SETTING: Ambulatory surgery center. METHODS: This paired-eye study evaluated patients who had implantation of a Tecnis AAB00 IOL with a continuous optic edge in 1 eye and an AcrySof SA60AT or SN60AT IOL with an interrupted optic edge in the fellow eye. Exclusion criteria were anterior capsule overlap onto the IOL optic of fewer than 360 degrees, neodymium:YAG laser capsulotomy, postoperative time fewer than 24 months or more than 30 months, pseudoexfoliation, glaucoma, history of iritis, and surgical complications that would affect the assessment of PCO. Posterior capsule opacification was assessed using the Evaluation of Posterior Capsular Opacification (EPCO) system on a scale of 0 (none) to 4 (severe opacity with a darkening effect). RESULTS: In 13 of 14 patients, the eye with the interrupted-edge IOL had a higher EPCO score than the eye with the continuous-edge IOL. The mean EPCO score was 0.39 and 0.08, respectively; the difference was statistically significant (P = .012). The PCO density was greater in eyes with the interrupted-edge IOL, with 35% having an EPCO score of 3 or 4; no eye with a continuous-edge IOL had a score that high. CONCLUSION: Eyes with an IOL with a continuous 360-degree square edge had significantly less PCO than eyes with an IOL with a square edge that was interrupted at the optic-haptic junction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".