Anti-VEGF therapy in pregnancy and breastfeeding
Bibliographic record
Abstract
Anti-vascular endothelial growth factor (VEGF) is the mainstay of treatment for several visually debilitating diseases and is considered the standard of care for a number of conditions which may affect younger patients, including women of childbearing age. These commonly include, but are not restricted to, diabetic macular edema (DME), proliferative diabetic retinopathy (PDR) and myopic choroidal neovascularization (CNV). As in other areas of medicine, pregnant and breastfeeding women are often excluded from clinical trials due to the unknown side effect profile of new drugs. This lack of evidence regarding the safety of anti-VEGF agents in pregnancy and breastfeeding introduces challenges for clinicians seeking to counsel these patients, particularly because anti-VEGF injections may be often used for an extended period of time, depending on the nature of the retinal disease. As a precaution, anti-VEGF injections are generally not recommended for women who are either pregnant or breastfeeding, given that they are considered Category C drugs and there is limited data regarding their excretion in human breast milk. Therefore, treatment of this group of patients is typically managed on a case-by-case basis, balancing the potential patient benefits with safety concerns for the infant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".