Characterization of Risk Factors for Calciphylaxis in Hemodialysis Patients in the Fraser Health Renal Program – A Matched Case-Control Retrospective Review
Bibliographic record
Abstract
Introduction: Calciphylaxis is a lethal and rare disease characterized by ischemic and necrotic skin lesions caused by vascular calcification of adipose tissue. There have been many risk factors analyzed in the literature; however, the pathogenesis of calciphylaxis is still not well understood and treatment options are limited due to the lack of interventional studies. Our objectives were to describe risk factors, prevalence, incidence, and outcomes for calciphylaxis in hemodialysis patients within the Fraser Health Renal Program. Methods: This was a retrospective matched case-control study of hemodialysis patients within the Fraser Health Renal Program. Hemodialysis patients with calciphylaxis were matched to hemodialysis patients without calciphylaxis in a 1:2 ratio for age and sex from September 2, 2017 to July 3, 2020. Findings: There was a total of 40 calciphylaxis cases matched to 80 controls. In the univariate analysis, peritoneal dialysis, higher body mass index, lower serum iron, lower transferrin saturation, sevelamer, cinacalcet, warfarin, iron (PO), and insulin were associated with increased risk of calciphylaxis. In the multivariate analysis, only peritoneal dialysis, serum iron, sevelamer, and warfarin were identified as significant and strong risk factors associated with calciphylaxis. A low prevalence of 1.9% and high mortality rate of 57.5% at 12 months was found for calciphylaxis cases. Discussion: Significant risk factors associated with calciphylaxis were peritoneal dialysis, serum iron, sevelamer, and warfarin. Future studies should further investigate the impact of minimizing exposure to these risk factors to reduce calciphylaxis development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".