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Record W1999508327 · doi:10.1016/j.sjopt.2013.01.002

Ranibizumab for idiopathic epiretinal membranes: A retrospective case series

2013· article· en· W1999508327 on OpenAlexaff
Marwan A. Abouammoh, Michel J. Belliveau, David R.P. Almeida, Jeffrey Gale, Sanjay Sharma

Bibliographic record

VenueSaudi Journal of Ophthalmology · 2013
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsQueen's UniversityHotel Dieu Hospital
Fundersnot available
KeywordsMedicineRanibizumabSeries (stratigraphy)OphthalmologySurgery

Abstract

fetched live from OpenAlex

PURPOSE: To study the effect of intravitreal ranibizumab on idiopathic epiretinal membranes (ERMs). METHODS: A retrospective cohort study on a consecutive series of ranibizumab intravitreal injections for epiretinal membranes was performed. Four cases were identified by reviewing a claims database linked to electronic medical records. All patients received a total of three 0.05 mg/0.05 ml ranibizumab intravitreal injections at a monthly interval. The primary outcome measure was the final best-corrected visual acuity (BCVA) at the end of the injection series, and the final central macular thickness (CMT). RESULTS: All four patients completed 3 months follow-up after the last ranibizumab injection. The mean baseline CMT was 509 microns (SD = 111). A trend was noticed for reduction in CMT (Δ = 41 microns) P = 0.08. Three patients improved by one line in their BCVA. The remaining patient maintained the same BCVA. No complications were noted. CONCLUSION: In this study, intravitreal injection of ranibizumab marginally reduced retinal thickness in four patients with minimal improvement in visual acuity. No safety concerns were noticed. Further basic science and clinical studies may be warranted to assess the role of vascular endothelial growth factor and the effect of ranibizumab on idiopathic epiretinal membranes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 designCase report
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

Citations3
Published2013
Admission routes1
Has abstractyes

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