A Meta-Analysis of Neurodevelopmental Outcomes following Intravitreal Bevacizumab for the Treatment of Retinopathy of Prematurity
Bibliographic record
Abstract
BACKGROUND: Retinopathy of prematurity (ROP) is the most common cause of preventable blindness in preterm infants. First-line treatments include intravitreal bevacizumab (IVB) or laser photocoagulation (LPC). OBJECTIVES: The aim of the study was to evaluate neurodevelopmental safety of IVB compared to LPC for ROP. METHODS: MEDLINE, Embase, and Cochrane library were searched up to September 2022. Studies were included with at least 12-month follow-up of primary outcomes such as severe neurodevelopmental impairment (sNDI), cerebral palsy (CP), and hearing impairment (HI). Secondary outcomes were moderate-to-severe neurodevelopmental impairment (msNDI), Bayley Scores of Infant Development (BSID-III), and visual impairment. RESULTS: 1,231 patients from 11 comparative studies were included. Quality of evidence was rated low for all outcomes. IVB was associated with a higher risk for sNDI (risk ratio [RR] = 1.25, 95% confidence interval [CI]: [1.01, 1.53], p = 0.04); and CP (RR = 1.40, CI: [1.08, 1.81], p = 0.01) compared to LPC. There was no significant difference between IVB and LPC for msNDI (RR = 1.15, CI: [0.98, 1.35], p = 0.08) and HI (RR = 1.43, CI: [0.86, 2.39], p = 0.17). BSID-III percentile scores were similar between IVB and LPC, with weighted mean differences of 1.51 [CI = -1.25, 4.27], 2.43 [CI = -1.36, 6.22], and 1.97 [CI = -1.06, 5.01] for cognitive, language, and motor domains, respectively (p > 0.05). CONCLUSION: To our knowledge, this is the largest meta-analysis on neurodevelopmental outcomes and the first to rigorously examine IVB monotherapy in ROP treatment. Compared to LPC, there was a marginally increased risk for sNDI and CP with IVB but little or no difference in the risk of msNDI and HI. Further randomized studies are needed to strengthen these findings.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".