81: Neurodevelopmental Outcomes of Extremely Preterm Infants Treated with Bevacizumab for Severe Retinopathy of Prematurity
Bibliographic record
Abstract
Intravitreal injection of bevacizumab, a vascular endothelial growth factor inhibitor (VEGF), is used to treat retinopathy of prematurity (ROP). As bevacizumab can diffuse into the systemic circulation, potential long-term effect on brain development needs to be documented. To compare neurodevelopmental outcomes at 18–22 months of preterm infants treated with bevacizumab versus laser. Data from the Canadian Neonatal Network and the Canadian Neonatal Follow-Up Network databases were retrospectively reviewed. A total of 114 infants born at <29 weeks gestational age (GA) in 2010–2011 with severe ROP (≥ stage 3 or plus disease) requiring treatment and followed at 18–22 months corrected age (CA) were studied. Neurodevelopmental outcome was assessed using the Bayley Scales 3rd edition. Regression analyses were performed. Of the 114 infants, 32 had bevacizumab (GA 24.8±1.5 weeks, birth weight 740±160 g) and 82 had laser (GA 24.8±1.3 weeks, birth weight 711±132 g). Neonatal characteristics differed between the bevacizumab vs. laser therapy groups for male sex (62% vs. 42%), SNAP-II score (24 vs. 18), and late-onset sepsis (62% vs. 44%). Bevacizumab treated infants had lower motor scores after adjustment for potential confounders (table). Preterm infants treated with bevacizumab had lower motor scores compared to those treated with laser therapy. There was no difference in cognition and language scores. Further investigation on the long-term safety of anti-VEGF treatment for ROP is needed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".