Severe Hypercalcaemia – Chronic Tophaceous Gout as the Responsible Cause?
Bibliographic record
Abstract
The association of chronic tophaceous gout with severe hypercalcaemia is exceptional. In this case, a 42-year old man with a long-standing history of gout arrived at the emergency room with altered mental status. Laboratory work up revealed a uric acid of 14.0 mg/dl, corrected calcium of 14.5 mg/dl, phosphorous of 6.3 mg/dl, parathyroid hormone (PTH) was suppressed (<3.0 pg/ml), 25-dihydroxyvitamin D 25.2 ng/ml, parathyroid hormone related-protein (PTHrP) was 45.0 pg/ml and calcitriol 19.6 pg/ml. Biopsy histopathology result showed deposits of monosodium urate crystals surrounded by granulomatous inflammation. The association of chronic tophaceous gout with severe hypercalcaemia is extremely rare and has been usually described to be secondary to 1-25 dihydroxyvitamin D (calcitriol) secretion. In this case, calcitriol levels were normal and this possibility was excluded. On the other hand, PTHrP had never been, until now, described as the responsible cause of hypercalcaemia in gout. In our case, baseline PTHrP and calcium values were elevated and after medical treatment both returned to normal values. PTHrP usually causes hypophosphataemia and in this case the abnormal renal function could have diminished this last effect.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".