VOLUMETRIC ASSESSMENT OF THE RESPONSIVENESS OF PIGMENT EPITHELIAL DETACHMENTS IN NEOVASCULAR AGE-RELATED MACULAR DEGENERATION TO INTRAVITREAL BEVACIZUMAB
Bibliographic record
Abstract
In Brief Purpose: To determine baseline factors that can predict the response of pigment epithelial detachments (PEDs) in neovascular age-related macular degeneration to treatment with intravitreal bevacizumab (IVB). Methods: Patients with newly diagnosed neovascular age-related macular degeneration and PED who were treated exclusively with IVB were included. Response to treatment was defined by change in PED volume (determined using spectral-domain optical coherence tomography). PEDs were classified as either predominantly serous or fibrovascular. Multivariable regression and receiver operating characteristic analyses were performed. Results: A total of 48 eyes were identified (mean follow-up time 73 weeks). Overall, the response to the first IVB treatment was predictive of the response to treatment at the final visit (P = 0.015). Serous PEDs had a greater decrease in volume at the final visit (P = 0.008). With respect to both PED types, a decrease in PED volume of 21% after the first IVB treatment was predictive of an overall decrease in volume of 30% at the final visit (sensitivity 83%, specificity 76%). Conclusion: In neovascular age-related macular degeneration, serous PEDs respond more favorably to IVB than fibrovascular PEDs. Overall, for both types of PED, the response to the first treatment is predictive of the final response to treatment. Taken together, the results would suggest that if there is less than 21% reduction in PED volume after the first IVB treatment, and/or the PED is predominantly fibrovascular, then switching to another antivascular endothelial growth factor agent should be considered. The authors used OCT-based volumetric assessment to determine factors that predict response of pigment epithelial detachments in neovascular age-related macular degeneration to treatment with intravitreal bevacizumab. Predominantly serous pigment epithelial detachments responded more favorably. Also, the initial response to the first treatment was predictive of the overall final response to treatment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".