Iron Supplementation After Blood Donation Expedites Hematological Recovery but Does Not Influence Exercise Performance
Bibliographic record
Abstract
ABSTRACT: Judd, TB, Shaw, KA, Krentz, JR, and Chilibeck, PD. Iron supplementation after blood donation expedites hematological recovery but does not influence exercise performance. J Strength Cond Res 39(6): 660-665, 2025-While the impact of blood donation on hemoglobin and exercise performance and the timeline for recovery is well studied, the role of iron supplementation in expediting recovery of performance is unknown. The objective of this research was to assess the effectiveness of oral iron supplementation in enhancing recovery of hemoglobin, hematocrit, and exercise performance after blood donation. Hemoglobin, hematocrit, and 5-km time trial performance were assessed in 10 moderately active subjects (6 men, 4 women; age = 34.0 ± 7.6 years, body mass = 74.4 ± 12.5 kg, V̇ o2 peak = 50.5 ± 6.0 ml·kg -1 ·min -1 ) before blood donation, the day after, and at weekly intervals for 5 weeks after donation. Before donation, individuals were stratified by sex and randomly assigned to supplement with 60 mg of elemental iron (3 men, 2 women) or placebo (3 men, 2 women) for 5 weeks. Significance was as accepted at p < 0.05. Time trial performance was decreased the day after donation by 6.7% ( p < 0.001) and returned to baseline levels by 1 week after blood donation with no difference between groups. Hemoglobin concentration decreased by 1.6 g·dl -1 after blood donation ( p < 0.01) with no difference between groups and failed to return to baseline after 5 weeks in either group. Hematocrit decreased by 4.0 and 3.1% in the iron and placebo groups, respectively, the day after donation compared with baseline ( p < 0.001). By week 4, hematocrit in the iron group was no longer different from baseline ( p = 1.0) but did not return to baseline values by week 5 in those supplementing with placebo ( p < 0.05). Iron supplementation may enhance hematological recovery after blood donation but does not influence recovery of endurance performance.
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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) | 0.002 | 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".