Intraocular lens capture in combined cataract extraction and pars plana vitrectomy: Comparison of 1-piece and 3-piece acrylic intraocular lenses
Bibliographic record
Abstract
PURPOSE: To report and compare the incidence of pupillary capture and posterior synechiae formation after combined cataract extraction and pars plana vitrectomy (PPV) with a 1-piece versus a 3-piece acrylic intraocular lens (IOL). SETTING: Royal Alexandra Hospital Eye Clinic, University of Alberta, Edmonton, Alberta, Canada. DESIGN: Comparative case series. METHODS: Consecutive patients who had combined cataract extraction with PPV were retrospectively reviewed. The outcomes in patients who received a 1-piece acrylic IOL and those who received a 3-piece acrylic IOL were compared. The proportion of patients with pupillary IOL capture and/or posterior synechiae postoperatively was recorded. RESULTS: The cohort comprised 145 patients. All cases of IOL capture occurred in eyes with a 1-piece IOL (n = 7; 7.7%); the difference between the 1-piece IOL group and the 3-piece IOL group was statistically significant (P = .043). There was no significant difference between the 2 IOL types in the rate of posterior synechiae formation. Regression analysis showed that the odds of posterior synechiae formation were significantly higher in cases in which perfluoropropane (C(3)F(8)) (odds ratio [OR], 24.01; P = .006), sulfur hexafluoride (SF(6)) (OR, 25.23; P = .007), or silicone oil (OR, 47.78; P<.001) was used. CONCLUSIONS: The incidence of IOL capture was significantly greater after implantation of a 1-piece IOL than after implantation of a 3-piece IOL during combined cataract extraction and PPV. Posterior synechiae formation was associated with the use of silicone oil, SF(6), or C(3)F(8).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".