MétaCan
Menu
Back to cohort
Record W2092122582 · doi:10.1097/icu.0b013e3283548459

Anterior segment uses of bevacizumab

2012· review· en· W2092122582 on OpenAlexaff
Irit Bahar, Sonia N. Yeung, Ruti Sella, Allan R. Slomovic

Bibliographic record

VenueCurrent Opinion in Ophthalmology · 2012
Typereview
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineBevacizumabNeovascularizationCorneal neovascularizationOphthalmologyVascular endothelial growth factorDermatologySurgeryVEGF receptorsInternal medicineAngiogenesisChemotherapy

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: A significant recent advancement in the treatment of neovascularization of the anterior segment of the eye is the development of antivascular endothelial growth factor (anti-VEGF) therapeutic agents.We present a review of the current knowledge on anti-VEGF therapy with bevacizumab for anterior segment neovascularization. RECENT FINDINGS: A review of the recent peer-reviewed literature reveals an increasing number of experimental and clinical studies on the use of Avastin in both human and animal eye models. Although the numbers are still relatively small, the evidence suggests that bevacizumab may be effective in the treatment of corneal and iris neovascularization. Its effect on primary and recurrent pterygium is more controversial. In general, achievement of vessels regression is usually partial, and recurrence may occur after cessation of treatment. Response to treatment is affected by the chronicity of vessels, their extent, the cause for blood vessels formation, and the route of administration. SUMMARY: Effective short-term response together with high patient tolerance to local bevacizumab therapy offer encouraging results for the management of anterior segment neovascular disorders. Although statistically significant regression of vessels has been documented in many studies, the clinical significance of this finding is still a subject of debate.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0010.000

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 head0.285
GPT teacher head0.471
Teacher spread0.186 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in OphthalmologySame topicCorneal Surgery and TreatmentsFrench-language works237,207