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The evidence: the role of antibiotics in intravitreal injections

2014· article· en· W2056016806 on OpenAlexaff
Wai‐Ching Lam

Bibliographic record

VenueActa Ophthalmologica · 2014
Typearticle
Languageen
FieldMedicine
TopicOcular Infections and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineEndophthalmitisAntibioticsMacular degenerationComplicationOphthalmologyIncidence (geometry)Vascular occlusionSurgery

Abstract

fetched live from OpenAlex

Abstract The current management of many retinal conditions, including age related macular degeneration, retinal vascular occlusion, and diabetic macular edema is not curative and requires prolonged monthly intravitreal injections. The most severe complication of this procedure is endophthalmitis and accordingly, more than two thirds of retinal specialists reported the use of topical antibiotics post‐ injection in a recent survey. However, there is a lack of evidence to demonstrate the effectiveness of topical antibiotics in reducing the risk of post‐injection endophthalmitis. We reported a large, multicentre, retrospective consecutive case series, the incidence of endophthalmitis following intravitreal injections in association with different post‐injection antibiotic practices. We found that the omission of routine topical antibiotic post‐injection did not produce a pronounced increase in endophthalmitis rates, suggesting that the use of topical antibiotic post‐injection might be unnecessary. In fact, the use of antibiotic prophylaxis, both immediately after the injection and for five days post‐injection is associated with greater rates of endophthalmitis, than without antibiotics.

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)0.019
metaresearch head score (Gemma)0.151
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.151
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.005
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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 designSystematic review
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

Citations0
Published2014
Admission routes1
Has abstractyes

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