Deferiprone exerts a dose‐dependent reduction of liver iron in adults with iron overload
Bibliographic record
Abstract
OBJECTIVE: While doses of deferiprone up to 75 mg/kg/d have been demonstrated to be effective in cardiac iron removal, their efficacy in the reduction of liver iron has been equivocal. The aim of this study was to evaluate the effect of deferiprone dose on liver iron concentrations in adult iron overload patients. METHODS: A single-centered, retrospective, cohort observational study was conducted involving 71 patients exposed to deferiprone doses up to 113 mg/kg/d between January 2009 and June 2015 for a median of 33 months. RESULTS: At the end of the study period, liver iron measured by R2 MRI was reduced by a mean 1.7 mg/g dw. A dose effect was observed, with incremental reductions of 2.8 mg/g dw in end of study LIC for every 10 mg/kg/d higher dose of deferiprone (P < 0.001). A dose effect was also observed in end of study ferritin and cardiac iron concentration measured by T2* MRI (P < 0.0001 and P = 0.048, respectively). No associations between adverse effects and deferiprone dose were observed, but there was a trend toward higher rates of agranulocytosis at higher doses and two of three hereditary hemochromatosis patients developed this complication. CONCLUSION: The present study failed to demonstrate that the use of deferiprone at >90 mg/kg/d was associated with increased risk of agranulocytosis or neutropenia, but did demonstrate more effective liver iron control in iron overload patients.
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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) | 0.000 | 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) | 0.000 | 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".