Bibliographic record
Abstract
In this review, the authors present special considerations a vitreoretinal surgeon should take into account before embarking on surgery in a pediatric eye. First, the anatomy of a pediatric eye is different from an adult and changes as the child grows. This is important especially in relation to the placement of transconjunctival ports. The structural characteristics of the sclera are also different, with lower scleral rigidity found in pediatric eyes. When considering vitrectomy, a posterior pars plicata lens-sparing technique should be considered. However, this may not be possible in complicated total detachments where anterior translimbal vitrectomy may be the method of choice. Scleral buckles are preferred for certain cases, and division of the encirclage is advocated in children below the age of 2 years, once the retina has stabilized. Enzymatic vitreolysis has been described as a preoperative adjunct to enhance complete detachment of the posterior hyaloid and reduce iatrogenic retinal breaks. However, its use in pediatric eyes has been limited, and larger studies are warranted. Finally, postoperative visual rehabilitation and treatment of amblyopia are key to maximizing functional outcomes in the pediatric patient. Co-management with a pediatric ophthalmologist and enlisting the co-operation of the parents are essential.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".