Calciphylaxis: Seven New Cases
Bibliographic record
Abstract
BACKGROUND: Calciphylaxis is a rare condition occurring most frequently in patients with end-stage renal disease (ESRD). It is characterized by vascular calcifications with a large variety of skin lesions. Even though this entity was first reported almost 50 years ago, the pathogenesis is still not well understood. OBJECTIVE: Having retrieved seven new cases from a single tertiary care hospital, the disease occurs probably more frequently than reported until now. The potential mechanism of action in this disease is discussed, particularly the hypercoagulability state. We also review potential treatments described in the literature. METHODS: Seven patients with calciphylaxis that occurred at the Hôtel-Dieu hospital between 1992 and 1998 were identified and their case histories reviewed and analyzed. CONCLUSION: Although hyperparathyroidism and imbalance of calcium-phosphorus homeostasis are paramount for calciphylaxis to occur, other mechanisms must be involved because the disease manifests itself in only a minority of ESRD patients. As the majority were under anticoagulation therapy and as we found abnormalities of the coagulation pathway in one patient, we suggest emphasizing these phenomena in the future. Along with evaluation of putative risk factors (abnormalities of the calcium:phosphate axis, diabetes), a detailed evaluation of the coagulation system should be done in every patient with calciphylaxis until more data are available.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".