Successful Treatment of Dialysis Osteomalacia and Dementia, Using Desferrioxamine Infusions and Oral 1-Alpha Hydroxycholecalciferol
Bibliographic record
Abstract
A 54-year-old patient with fracturing dialysis osteomalacia and dementia demonstrated rapid deterioration following parathyroidectomy which was performed for sustained hypercalcemia. Reduction of the total body aluminum burden was attempted using desferrioxamine (DFO) as a chelating agent. After 6 months, DFO infusion resulted in sustained clinical remission of both neurological and skeletal symptoms, associated with an improvement in the EEG and improved mineralization of bone. A reduction in total body aluminum burden was reflected by reduced skeletal aluminum content, quantitated histochemically in iliac crest bone biopsies before and after DFO therapy. Dramatic increases in serum aluminum levels were documented in the initial weeks of DFO therapy leading to increased removal of aluminum during dialysis; in vitro studies indicated that the ultrafiltrable fraction of serum aluminum increased from 17 to more than 60% after initiating DFO treatment. However, after 6 months of therapy, serum aluminum levels remained unchanged after DFO infusion. These findings suggest that the serum aluminum response to DFO infusion might be a useful reflection of the total-body aluminum burden and also a reflection of the adequacy of a chelation program designed to reduce whole-body aluminum content.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".