Bibliographic record
Abstract
PURPOSE OF REVIEW: This article highlights recent advances in our understanding of the incidence, epidemiology, clinical presentation, evaluation, diagnosis, treatment, and prognosis of parathyroid carcinoma. RECENT FINDINGS: The prevalence of parathyroid carcinoma is approximately 0.005% of all cancers. Therefore, parathyroid carcinoma is one of the rarest malignancies known. Patients with parathyroid carcinoma present with clinical symptoms of hypercalcaemia as these cancers are usually hormonally functional. It is not uncommon that patients present with complications of profound hypercalcaemia because of an elevated parathyroid hormone. Parathyroid carcinoma is difficult to diagnose preoperatively unless patients present with metastatic disease. Serum calcium often exceeds 14 mg/dl and serum parathyroid hormone is significantly elevated commonly between three and 10 times of the upper limit. Fine needle aspiration is not recommended because of the risk of parathyromatosis. Treatment includes surgery as a primary form of therapy and this usually follows with postoperative radiotherapy, although its use remains controversial. SUMMARY: Patients with parathyroid carcinoma should undergo adequate surgical excision with an attempt of preserving vital structures such as the recurrent laryngeal nerve. Often en bloc resection of the ipsilateral thyroid lobe with comprehensive level VI dissection is required. Postoperative radiotherapy should be considered in most cases.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.016 |
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".