Symmetrical craniofacial hypertrophy in patients with tertiary hyperparathyroidism and high‐dose cinacalcet exposure
Bibliographic record
Abstract
We are reporting on a series of two patients with end-stage renal disease on hemodialysis, presented for surgical parathyroidectomy secondary refractory hyperparathyroidism. Both patients had failed maximized medical managements, including higher-than-usual doses of the calcimimetic cinacalcet (270 and 180 mg/day, respectively). On physical exam, both patients had marked symmetrical craniofacial hypertrophy with coarse distortion of facial features, similar in appearance to past reports of Sagliker syndrome. On X-ray and computed tomographic exam, they had peculiar areas of bone absorption on the skull, imitating the radiologic appearance of multiple myeloma. Bone biopsy of the maxilla, however, did not show the expected brown tumor, but rather described only fibrosis and reactive bone formations. This phenotype developed while being on cinacalcet, progressed despite escalation of therapy, and improved only after parathyroidectomy. Both patients developed massive "hungry bone syndrome" after parathyroidectomy necessitating prolonged i.v. calcium infusion. This pattern of severe facial distortion likely represented an adverse consequence of severe tertiary hyperparathyroidism, along with supraphysiologic dose of cinacalcet administration and 25-hydroxy vitamin D deficiency in sensitive individuals. The genetic base of this observation remained unexplained.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".