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Record W4411994935 · doi:10.70070/xcyxt302

What are the most effective medical interventions for managing retinopathy of prematurity in preterm infants born ? : A Systematic Review

2025· review· en· W4411994935 on OpenAlexaff
Roysam Azmal sitanggang, Sita Pradjnadewi

Bibliographic record

VenueThe International Journal of Medical Science and Health Research · 2025
Typereview
Languageen
FieldMedicine
TopicRetinopathy of Prematurity Studies
Canadian institutionsKelowna General Hospital
Fundersnot available
KeywordsRetinopathy of prematurityMedicinePsychological interventionPediatricsIntensive care medicineGestational agePregnancyNursing

Abstract

fetched live from OpenAlex

Introduction: Retinopathy of Prematurity (ROP) is a leading cause of preventable childhood blindness affecting preterm infants. Laser photocoagulation, the traditional standard of care, is effective but inherently destructive, leading to permanent peripheral visual field defects and a high incidence of myopia. The introduction of anti-Vascular Endothelial Growth Factor (VEGF) agents like bevacizumab offers a less destructive approach with the potential for better refractive outcomes. However, concerns regarding disease recurrence and potential systemic effects persist. This systematic review was conducted to evaluate and synthesize current evidence to determine the most effective medical interventions for ROP. Methods: This systematic review adhered to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. A comprehensive search was performed across PubMed, Semantic Scholar, Springer, and Google Scholar. Twenty-seven studies, including randomized controlled trials and comparative studies evaluating anti-VEGF therapies and laser photocoagulation, were included. The primary outcomes analyzed were disease regression, recurrence rates, and long-term structural and refractive outcomes. Results: The evidence consistently showed that both anti-VEGF therapy and laser photocoagulation are highly effective in achieving initial disease regression. A significant advantage for anti-VEGF therapy is more favorable long-term refractive outcomes, particularly a significantly lower incidence of high myopia compared to laser. However, this is counterbalanced by a variable but significant risk of disease recurrence following anti-VEGF monotherapy, a risk that is lower with laser treatment. Evidence also suggests clinical differences between agents, with one study finding a lower recurrence rate for bevacizumab compared to aflibercept. Conclusion: The optimal management for ROP requires balancing significant trade-offs. Anti-VEGF therapy is often the superior choice for posterior disease (Zone I) and offers the compelling benefit of better long-term vision by reducing high myopia. Conversely, laser photocoagulation provides a more definitive treatment with lower recurrence rates but at the known cost of peripheral vision. Combination strategies are emerging to leverage the strengths of both modalities. Ultimately, the treatment decision must be individualized, weighing the risk of recurrence and unknown systemic effects of anti-VEGF against the certainty of peripheral field loss and myopia from laser.

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)0.005
metaresearch head score (Gemma)0.023
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: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.012
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.239
GPT teacher head0.578
Teacher spread0.339 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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