Reverse Optic Capture to Stabilize a Toric Intraocular Lens
Bibliographic record
Abstract
PURPOSE: To describe a technique for stabilizing a rotationally unstable toric intraocular lens (IOL). METHOD: Case report and literature review. RESULTS: Surgical technique and long-term follow-up for a patient who underwent repositioning and stabilization of a mobile 1-piece acrylic toric IOL using reverse optic capture (ROC) are described. This patient presented with early, more than 70° off-axis rotation. The IOL was repositioned but was very mobile within the bag and tended to rotate off-axis; hence, it was stabilized in the desired position by capturing the optic through the anterior continuous curvilinear capsulorhexis, leaving the haptics in the bag. The immediate and 2-year postoperative follow-up revealed a stable and on-axis IOL with no visual, refractive or ocular complications. CONCLUSIONS: ROC is a useful and safe technique to address the problem of toric IOLs that tend to rotate at the time of surgery or are not stable postoperatively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".