Long-term outcomes of iris-sutured subluxated intraocular lenses
Bibliographic record
Abstract
PURPOSE: This study evaluated the long-term outcomes of managing posterior chamber intra-ocular lens (IOL) (PCIOL) subluxation through pars plana vitrectomy (PPV) with IOL iris suturing. SETTINGS AND DESIGN: Retrospective chart review. METHODS: Patients who underwent PPV with iris-sutured IOL (IS-IOL) for IOL subluxation between January 2008 and April 2021 at a tertiary center with a minimum of 6 months of follow-up were included. The patients were divided into two groups: those who had prior PPV and those who had not undergone the procedure. RESULTS: A total of 54 patients underwent iris suturing of a subluxated IOL. Among them, 36 (66%) had previously undergone PPV, while 18 patients (33%) had not. The etiology of PCIOL subluxation was uncertain in 20 (37.0%), prior PPV in 17 (32%), and following complicated cataract surgery in 11 (20%) cases. The mean time between original IOL insertion and IS-IOL was 6.1 ± 7.0 years. The mean follow-up duration was 46.8 ± 39.7 months. The mean post-operative best corrected visual acuity (BCVA) was logMAR 0.43 ± 0.52 at final follow-up, a significant improvement from pre-operative BCVA. Vision was significantly better in the group with no prior PPV (logMAR 0.54 ± 0.59 vs. 0.21 ± 0.23 at final follow-up, P = 0.026). At final follow-up, 34 (63%) eyes had BCVA of 20/40 or better. The most common complication was cystoid macular edema, attributed to the IS-IOL in 13 (21.4%) eyes, 11 (68.6%) of which resolved or improved. CONCLUSIONS: The management of posterior chamber IOL subluxations with PPV and iris suturing of the subluxated IOL is a safe technique that provides excellent long-term visual outcomes.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".