Ocular motility disturbances after glaucoma drainage device implantation for paediatric glaucoma: a cross-sectional study
Bibliographic record
Abstract
AIM: To grade extraocular motility in the field of action of each extraocular muscle following superotemporal glaucoma drainage device (GDD) implantation in a paediatric population and to investigate which drainage device (Ahmed vs Baerveldt) yields less extraocular motility disturbance. METHODS: Cross-sectional study of children with a GDD implanted consecutively by a single surgeon who underwent ocular motility examination by two masked orthoptists. Ductions in the cardinal positions were graded. Ocular alignment, visual acuity, binocularity, stereopsis and intraocular pressure were also measured, and patient charts were reviewed. RESULTS: Thirty children each had one eye included. Twenty-one eyes had an Ahmed GDD and 9 had a Baerveldt GDD. Mean time between GDD insertion and ocular motility exam was 68 months in the Ahmed group and 19 months in the Baerveldt group. Exotropia was present in 46% and vertical heterotropia in 46% of children post-GDD insertion. Thirty-three percent of eyes had a moderate or severe limitation of elevation in abduction, 30% of elevation in adduction, 10% of abduction and 10% of adduction. There was a trend towards more eyes in the Ahmed group (62%) having at least a moderate limitation in ocular motility (-2 or worse; scale -1 to -4) compared with the Baerveldt group (22%). CONCLUSION: Strabismus is common in children with GDDs. Our motility and alignment findings are consistent with either a mass effect of the device and bleb and/or scarring beneath the plate in the quadrant of the GDD causing dysmotility, most commonly limitation towards the GDD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".