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Record W4406607168 · doi:10.1016/j.oret.2025.01.012

A Meta-Analysis of Intravitreal Ranibizumab versus Laser Photocoagulation for the Treatment of Retinopathy of Prematurity

2025· review· en· W4406607168 on OpenAlexafffund
Abed Baiad, Catherine Q. Sun, Grace Yin, Marko M. Popovic, Rajeev H. Muni, Kamiar Mireskandari, Peter J. Kertes

Bibliographic record

VenueOphthalmology Retina · 2025
Typereview
Languageen
FieldMedicine
TopicRetinopathy of Prematurity Studies
Canadian institutionsSunnybrook Health Science CentreSt. Michael's HospitalUniversity of TorontoMcMaster UniversityQueen's UniversityHospital for Sick ChildrenUniversity of British Columbia
FundersMcGill University
KeywordsRetinopathy of prematurityMedicineRanibizumabOphthalmologyOptometryBevacizumabSurgeryGestational agePregnancy

Abstract

fetched live from OpenAlex

PURPOSE: Laser photocoagulation (LPC) has been a traditional treatment for retinopathy of prematurity (ROP). However, intravitreal anti-VEGF agents such as bevacizumab and intravitreal ranibizumab (IVR) have also been increasingly used. This meta-analysis aims to rigorously compare IVR to LPC in the treatment of ROP. DESIGN: Meta-analysis. PARTICIPANTS: One thousand nine hundred forty-seven eyes from 1007 infants were included. METHODS: Medline, Embase, and Cochrane CENTRAL were used to identify studies comparing IVR monotherapy to LPC (PROSPERO ID: CRD42023390855). The primary outcome was ROP regression. Secondary outcomes included likelihood of additional treatment, time from treatment to reactivation or retreatment, refractive outcomes, and adverse events such as retinal detachment, cataract, macular dragging/ectopia, vitreous or retinal hemorrhage, glaucoma, and endophthalmitis. A random-effects meta-analysis was designed. RESULTS: A total of 2361 articles were identified. One thousand nine hundred forty-seven eyes from 7 cohort studies, 1 case-control study, and 2 randomized controlled trials were included with a median follow-up of 21 months (range, 11-75 months). There was no significant difference in disease regression between IVR and LPC (risk ratio [RR], 0.96; 95% confidence interval [CI], 0.83-1.10; P = 0.52); however, eyes that underwent IVR were associated with a higher likelihood of requiring additional treatment (RR, 2.70; CI, 1.55-4.68; P < 0.001). Although less frequent, retreatment occurred earlier with LPC compared with IVR (weighted mean difference [WMD], -4.29 weeks; CI, -6.48 to -2.10; P < 0.001). Furthermore, eyes that received IVR had a lower refractive error, with a WMD of -0.93 diopters (CI, -1.54 to -0.32; P = 0.003) at a median age of assessment of 5.0 years (range, 1.5-6.3 years). There was no difference in the rate of adverse events between LPC and IVR (P > 0.05 for RD, MDR, VH, and cataract). Quality of evidence was rated moderate for likelihood and time of additional treatment, as well as refractive error, but was considered low for disease regression and adverse events. CONCLUSIONS: Compared with LPC, IVR was associated with a higher likelihood of requiring additional treatment but a lower risk of myopia. More studies are needed to evaluate dose-response relationships and temporal trends in ROP regression after these treatments. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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)0.017
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.031
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.062
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.242
GPT teacher head0.437
Teacher spread0.195 · 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 designMeta-analysis
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
Published2025
Admission routes2
Has abstractyes

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