Multimodal imaging of combined hamartoma of the retina and retinal pigment epithelium associated with an acquired vitelliform lesion
Bibliographic record
Abstract
BACKGROUND: We present a case of a combined hamartoma of the retina and retinal pigment epithelium associated with a subfoveal acquired vitelliform lesion induced by vitreomacular traction. The purpose of this report is to present a unifying hypothesis of these concurrent findings, as aided by multimodal imaging. CASE PRESENTATION: A 25-year-old white man presented with a 6-month history of a visual disturbance in his left eye. At presentation, ophthalmic assessment showed a combined hamartoma adjacent to his optic nerve that had caused marked corrugation within the inner retinal surface. An acquired vitelliform lesion was present in the macula with an associated epiretinal membrane as demonstrated on spectral-domain optical coherence tomography. Optical coherence tomography angiography corroborated the clinical diagnosis of combined hamartoma. CONCLUSIONS: We are not aware of previous cases of a combined hamartoma associated with an acquired vitelliform lesion. As previously proposed in acquired vitelliform lesions related to epiretinal membrane and vitreoretinal traction, we believe that macular tractional forces might interfere with retinal pigment epithelium phagocytosis of shed outer segments, leading to the occurrence of this acquired vitelliform lesion.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".