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Record W2907093056 · doi:10.1097/ijg.0000000000001163

Long-term Follow-up of Ahmed Glaucoma Valve Tube Position Changes

2018· article· en· W2907093056 on OpenAlexaff
David J. Mathew, A Anuradha, Stephanie A.W. Low, Avner Belkin, Yvonne M. Buys, Graham E. Trope

Bibliographic record

VenueJournal of Glaucoma · 2018
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineGlaucoma valveGlaucomaTerm (time)OptometryOphthalmologyPosition (finance)Tube (container)EngineeringAstronomy

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate long-term (4.5 to 6 y) changes in the position of Ahmed glaucoma valve (AGV) tubes. MATERIALS AND METHODS: Adult patients aged 18 years and above, 1 to 2 months post-AGV implantation were enrolled. Tube position was evaluated using anterior segment optical coherence tomography at baseline and final follow-up. The intracameral tube length (ICL), tube-cornea (TC) distance, and cornea-tube angle were measured. Wilcoxon-signed rank test was used to assess whether the changes in parameters from baseline were significant. RESULTS: In total, 11 eyes of 9 patients were included in the analysis. Mean duration of follow-up was 5.2±0.8 years (4.4 to 6.1 y). The ICL increased from 1.58±0.40 to 1.74±0.62 mm (P=0.18). The TC decreased from 0.36±0.12 to 0.29±0.05 mm (P=0.04). The cornea-tube angle decreased from 27.76±5.57 to 24.82±5.69 degrees (P=0.08). Overall, 73% of the tubes moved toward the cornea (mean 0.11 mm, over 4.4 to 6.1 y). In total, 73% showed an increase in ICL; 45% showed an increase of >0.3 mm [mean 0.50 mm (33%) increase]. Two of 11 tubes (18%) showed no significant change in the parameters (ICL, 0.03 and 0.01 mm increase; TC, 0 and 0.01 mm increase); these tubes were noted to lie on the iris. CONCLUSIONS: Tubes tend to move toward the cornea over time. To avoid corneal damage and involvement of the visual axis in the future, tubes should be reasonably short and inserted tangentially, preferably in the posterior one third of the anterior chamber.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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 teacher head, 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

Citations9
Published2018
Admission routes1
Has abstractyes

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