Simultaneous Bilateral Cataract Surgery in Premature Babies With and Without Retinopathy of Prematurity
Bibliographic record
Abstract
Background: Four premature babies (eight eyes) undergoing simultaneous bilateral cataract surgery are presented and discussed. Methods: All four babies underwent simultaneous bilateral cataract surgery. Three babies (six eyes) had primary implantation of posterior chamber intraocular lenses (IOLs) and one baby (two eyes) had primary lensectomies with secondary visual correction with contact lenses. Results: In all eight eyes, there was no endophthalmitis and no spontaneous choroidal hemorrhages. All eyes experienced large myopic shifts, as high as –15.00 D. All six eyes with IOLs required secondary membranectomies, which did not reoccur. Case 4 had Lowe’s syndrome, was bilaterally aphakic post-op, and subsequently developed glaucoma requiring bilateral glaucoma surgery. Conclusions: Simultaneous bilateral cataract surgery in severely premature babies can be successful in restoring vision over the long term. Strategies to successfully deal with the timing of surgery, IOLs, secondary membranes, secondary glaucoma, appropriate IOL powers, and IOL formulas is discussed. Successful long-term successful visual outcomes are now possible in this complex group of premature babies.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".