Long-term safety follow-up of an anterior chamber angle-supported phakic intraocular lens
Bibliographic record
Abstract
Purpose To report adverse device effects and annualized endothelial cell loss rate for up to 10 years after implantation of the Acrysof L-series Cachet phakic intraocular lens (pIOL). Setting Clinical centers in the United States, European Union, and Canada. Design Nonrandomized clinical trial. Methods After implantation of the pIOL, the endothelial cell density (ECD) at follow-up evaluations was compared with the 6-month postoperative baseline. Adverse device effects were assessed. Results This study assessed 638 patients (1087 eyes) from previous clinical trials. The mean central ECD change from baseline was −9.6% ± 8.3% (SD) (−1.7% annualized; 623 eyes) and −11.0% ± 9.9% (−1.7% annualized; 703 eyes) at 6 years and 7 years, respectively. The mean peripheral ECD change from baseline was −10.8% ± 8.7% (−2.0% annualized; 615 eyes) and −11.9% ± 10.0% (−1.8% annualized; 680 eyes), respectively. Endothelial cell loss greater than 30% from the preoperative baseline at any time after implantation affected 8.0% of all eyes. An ECD of 1500 cells/mm2 or less at any time after implantation affected 2.7% of all eyes. The most common adverse device effects were peripheral iris adhesions (57 eyes [5.2%]), corneal endothelial cell loss (42 eyes [3.9%]), and pIOL explantation (37 eyes [3.4%]). Conclusions Long-term evaluation of the pIOL showed a persistent ECD decrease in some eyes that was numerically larger than the annual rate expected with aging. Endothelial cell loss resulted in explantation in 3.1% of all eyes with the pIOL. Patients had no permanent vision loss. The manufacturer recommends that patients continue to be monitored and their corneal endothelium evaluated semiannually.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".