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Record W1980819693 · doi:10.1097/ijg.0b013e31817d23e0

Correlation Between the Indiana Bleb Appearance Grading Scale and Intraocular Pressure After Phacotrabeculectomy

2009· article· en· W1980819693 on OpenAlexaff
Michael Smith, Mary L. Chipman, Graham E. Trope, Yvonne M. Buys

Bibliographic record

VenueJournal of Glaucoma · 2009
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsBleb (medicine)MedicineOphthalmologyGrading scaleGlaucomaIntraocular pressureVascularityTrabeculectomyGrading (engineering)Surgery

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the relationship between bleb morphology, recorded using the Indiana Bleb Appearance Grading Scale (IBAGS), and intraocular pressure (IOP) after phacotrabeculectomy. METHODS: Two years postphacotrabeculectomy, a single observer compared bleb morphology to the IBAGS standard photographs in 76 eyes of 76 patients. In addition, the presence or absence of microcysts was recorded. IOP was also measured. RESULTS: On multivariate analysis increasing bleb height was associated with a low IOP (P=0.017). An increase in IBAGS height score by 1 U resulted in a reduction in IOP of 2.16 mm Hg (95% confidence interval=0.40-3.92 mm Hg). In this study, there was no association between vascularity, bleb extent or microcysts, and IOP. There were no cases of bleb leak in this series. CONCLUSIONS: Two years postphacotrabeculectomy increased bleb height, as measured by the IBAGS, was associated with a decrease in IOP, with a 1 point increase in IBAGS height score resulting in a decrease of 2.16 mm Hg. We found no association between bleb extent, vascularity, or the presence or absence of conjunctival microcysts. As there were no cases of bleb leak in this study this characteristic could not be evaluated.

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 score0.017
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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