Multimodality approach to treat calciphylaxis in end-stage kidney disease patients
Bibliographic record
Abstract
A multimodality approach has been proposed as an effective treatment for calciphylaxis in patients with end-stage kidney disease. In this retrospective study, we report the cases of 12 end-stage kidney disease patients from l’Hôtel-Dieu de Québec hospital (Canada) who were diagnosed with calciphylaxis between 2004 and 2012 and treated with a multimodality clinical approach including sodium thiosulfate (STS). Statistical analyses were performed to evaluate the impacts of patients characteristics, the different interventions as well as therapy regimen on the therapeutic response. The majority of patients (n = 9) were hemodialyzed. The patients-associated comorbidities were consistent with previously reported risk factors for calciphylaxis: Diabetes (n = 11), calcium-based phosphate binders use (n = 10), warfarin use (n = 9), obesity (n = 7), female gender (n = 8) and intravenous iron use (n = 8). STS was given for a median duration of 81 days. 75% of the patients had a response (total or partial) including a complete response in 42% of patients. One-year mortality rate was low (25%). STS was used during a mean duration of 83.33 ± 41.52 days and with a total cumulating dose of 1129.00 ± 490.58 g. The recorded mean time before a complete response was 102.20 days (51–143). Pain improvement occurred after a mean time of 8.67 ± 10.06 days. None of the studied factors was statistically associated with a complete or a partial response to the multimodality approach. Although our data have a limited statistical power, they support treating calciphylaxis with a multimodality approach including STS as its effects are independent from important clinical variables.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".