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Record W3211179072

Alternative Indications For Goniotomy In Pediatric Glaucoma

2006· article· en· W3211179072 on OpenAlexaff
Alejandra A. Valenzuela, Gordon R. Douglas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineGlaucomaHyphemaCongenital glaucomaIntraocular pressureRefractory (planetary science)Medical therapySurgeryRetrospective cohort studyMedical recordOphthalmologyGlaucoma surgery
DOInot available

Abstract

fetched live from OpenAlex

Purpose. To evaluate the safety and efficacy of goniotomy as a first-line surgery in cases of open angle pe-diatric glaucoma, other than primary congenital, in which medical therapy had failed or had been judged to be not advisable. Methods. A non-comparative retrospective chart review of a series of gonio-tomies performed in children with refractory secondary glaucoma. Success was defined as an intraocular pressure (IOP) less or equal to 22 mmHg, without need for further surgical intervention with or without additional medical therapy. Results. 12 patients (16 eyes) with underlying diagnoses of Sturge Weber Syndrome, uveitis, infantile and traumatic glaucoma were included. The mean age at the first goniotomy was 5.2-year-old, with a mean follow-up of 35 months. Surgical success was achieved in 9 eyes (56%) with a mean IOP of 16.3 + 4.61mmHg (reduction of 16 mmHg, p<0.001). Complications included different degrees of hyphema and a small iris prolapse. Discussion. Although traditionally limited to management of congenital glaucoma, goniotomy is a relatively gentle and potentially useful first-line surgical procedure for children with refractory glaucoma different than congenital.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.008
GPT teacher head0.267
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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