Ten-year safety follow-up and post-explant analysis of an anterior chamber phakic IOL
Bibliographic record
Abstract
PURPOSE: To assess endothelial cell loss (ECL) rate and collect safety data in patients with AcrySof L-series Cachet phakic intraocular lens (pIOL) up to 10 years post-implantation. SETTING: Clinical settings in the United States, European Union, and Canada. DESIGN: Nonrandomized, observational, open-label safety study. METHODS: Central and peripheral endothelial cell density was evaluated and compared with 6-month post-implantation baseline. Nonlinear analysis was performed to identify factors affecting post-explantation ECL. Additional evaluations included uncorrected visual acuity (UCVA), corrected distance visual acuity (CDVA), adverse device effects (ADEs), and serious adverse events (SAEs). RESULTS: The study included 1123 implanted eyes (mean age, 37.5 years). At 10 years, mean central and peripheral ECL was 16% (1.7% annualized). Explantations were performed in 10% of eyes (n = 136/1323). For eyes with pIOL explantation because of ECL (7%), annualized ECL rate post-explantation was numerically lower compared with the overall rate in eyes that underwent explantation for any reason (annualized rate, -1.65% vs -2.03%, respectively; n = 96) and compared with pre-explantation ECL. Mean ± SD CDVA and UCVA were -0.12 ± 0.11 and 0.03 ± 0.22 logarithm of the minimum angle of resolution, respectively. Common ocular ADEs included ECL (10%), pIOL extraction (9%), iris adhesion (7%), and pupillary deformity (2%). Common SAEs included pIOL extraction (11%), ECL (9%), and iris adhesions (8%). CONCLUSIONS: Cachet pIOLs were associated with long-term ECL in some cases. Overall, only 10% of all implanted eyes underwent explantation during 10-year follow-up. In patients requiring explantation because of ECL, the annualized ECL rates decreased post-explantation in some eyes. Continued monitoring of patients regardless of explantation is recommended.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".