The effects of intravenous iron supplementation on fatigue and general health in non-anemic blood donors with iron deficiency: a randomized placebo-controlled superiority trial
Bibliographic record
Abstract
We investigated whether intravenous iron supplementation improves fatigue and general health in non-anemic repeat adult blood donors with iron deficiency (ferritin ≤ 50 µg/L). Of 1,487 potentially eligible participants, 203 were randomly assigned to a single intravenous dose of 800 mg iron-carboxymaltose and 202 to placebo; 393 participants completed the trial. At 6 to 8 weeks after intervention, self-rated mean fatigue scores (numeric rating scale from 1-10, primary outcome) were 3.9 ± 1.8 in the iron supplementation group and 4.0 ± 2.2 in the placebo group, showing no group difference (p = 0.819). Pre-specified subgroup analyses of gender, ferritin < 25 µg/L and fatigue ≥ 4 points, as well as exploratory analyses of lower ferritin cut-offs did not reveal any between-group differences. In terms of secondary outcomes, the mean differences were 114.2 µg/L for ferritin (95% CI 103.1-125.3) and 5.7 g/L for hemoglobin (95% CI 4.3-7.2) with significantly higher values in the iron supplementation group. No group differences were observed for different measures of general well-being and other clinical and safety outcomes. Intravenous iron supplementation compared with placebo resulted in increase of ferritin and hemoglobin levels in repeat blood donors with low iron stores, yet had no effect on fatigue and general well-being.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".