Granulomatous reaction to injectable hyaluronic acid (Restylane) diagnosed by fine needle biopsy
Bibliographic record
Abstract
The hyaluronic acid (HA) derivative Restylane is now the most common injectable soft tissue filler used for facial wrinkle augmentation. Although it is generally well tolerated and absorbed within months, nodule formation at the injection site has been documented. A 62-year-old woman with a history of carcinoma of the breast six years previously was referred to a fine needle aspiration (FNA) clinic for biopsy of a subcutaneous facial nodule. On palpating the nodule six weeks prior to presentation she was referred for ultrasound examination; findings were reported as being consistent with a lymph node, raising concern of possible metastatic carcinoma of the breast. Serendipitously the same ultrasound examination led to discovery of a thyroid nodule that was aspirated and found to be papillary carcinoma, broadening the differential diagnosis of the facial nodule to metastatic thyroid carcinoma. On physical examination the lesion was a 1 cm subcutaneous nodule overlying the lower third of the mandible, a location felt to be consistent with a slightly “high” submental node. However, the nodule had irregular contours on palpation, and although it could be moved over the underlying bone, seemed to be fixed to the overlying skin. No cellular material was obtained by initial sampling with a 27G needle. After instillation of local anaesthetic, two samples were taken with a …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".