Assessment of refractive outcomes in eyes that underwent intraocular lens implantation in the posterior chamber but not “in-the-capsular bag:” A comparative retrospective study
Bibliographic record
Abstract
Abstract: PURPOSE: The purpose of this study was to report visual and refractive outcomes in eyes that underwent intraocular lens (IOL) fixation in the absence of capsular support. METHODS: This was a retrospective chart review of cases undergoing posterior chamber iris-fixated IOL (IFIOL) and scleral-fixated IOL (SFIOL) implants from June 2014 to March 2020 with more than 3 months of follow-up and having a preoperative best-corrected visual acuity of 20/80 and more. RESULTS: Records of 120 eyes of 112 patients were reviewed. The mean age of the patients was 46.9 ± 22.3 (14.4–98.0) years, and 62% ( n = 70) of participants were male. Most of the eyes (102: 85%) were aphakic at the time of surgery. The mean follow-up was 22.95 ± 17.1 months. The efficacy index of sutured IFIOL and glued SFIOL outperformed sutured SFIOL at 3 months and final visits postoperatively ( P < 0.001 ) . All techniques studied here resulted in a similar safety index at 3 months ( P = 0.4). The mean predictive error (postoperative spherical equivalent refraction minus intended target refraction) was +0.07 ± 1.5 D and −0.12 ± 1.4 D at 3 months and the final postoperative visit, respectively. CONCLUSION: The studied techniques have relatively good visual and refractive outcomes in this series. In addition, techniques involving a small corneal incision with foldable IOL fixation to the iris or scleral tissue have superior efficacy and safety indices compared to creating large corneoscleral wounds for rigid IOL fixation techniques.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".