Multiple cellular neurothekeomas in a middle‐aged woman including the lower extremity: A case report and review of the current literature
Bibliographic record
Abstract
Cellular neurothekeoma is a benign cutaneous neoplasm that typically occurs on the head, neck, and upper body of young adults with a slight female predominance. It is a rare lesion to diagnose and multiple neurothekeomas in one patient are even more uncommon finding. We present a case of multiple neurothekeomas in a middle-aged woman with lower extremity involvement and summarize the current literature on multiple neurothekeoma patients. A 46-year-old female presented with nearly one dozen skin-colored papules on the head, upper limb, and lower limb. The lesions were clinically diagnosed as dermatofibromas and a nevus. Eight lesions were biopsied and confirmed to be cellular neurothekeomas, with one initially misinterpreted on histology as a dermatofibroma. Awareness of cellular neurothekeoma as a diagnostic entity and the possibility of atypical presentations as seen in our case (eg, in multiple numbers, in older adults, and on the lower extremity) are important in allowing for accurate clinical and histological diagnosis of these lesions. The possibility of a syndromic association with multiple cellular neurothekeomas should be explored further.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".