Effect of iron supplementation on fatigue in nonanemic menstruating women with low ferritin: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The true benefit of iron supplementation for nonanemic menstruating women with fatigue is unknown. We studied the effect of oral iron therapy on fatigue and quality of life, as well as on hemoglobin, ferritin and soluble transferrin receptor levels, in nonanemic iron-deficient women with unexplained fatigue. METHODS: We performed a multicentre, parallel, randomized controlled, closed-label, observer-blinded trial. We recruited from the practices of 44 primary care physicians in France from March to July 2006. We randomly assigned 198 women aged 18-53 years who complained of fatigue and who had a ferritin level of less than 50 ug/L and hemoglobin greater than 12.0 g/dL to receive either oral ferrous sulfate (80 mg of elemental iron daily; n=102) or placebo (n=96) for 12 weeks. The primary outcome was fatigue as measured on the Current and Past Psychological Scale. Biological markers were measured at 6 and 12 weeks. RESULTS: The mean score on the Current and Past Psychological Scale for fatigue decreased by 47.7% in the iron group and by 28.8% in the placebo group (difference -18.9%, 95% CI -34.5 to -3.2; p=0.02), but there were no significant effects on quality of life (p=0.2), depression (p=0.97) or anxiety (p=0.5). Compared with placebo, iron supplementation increased hemoglobin (0.32 g/dL; p=0.002) and ferritin (11.4 μg/L; p<0.001) and decreased soluble transferrin receptor (-0.54 mg/L; p<0.001) at 12 weeks. INTERPRETATION: Iron supplementation should be considered for women with unexplained fatigue who have ferritin levels below 50 μg/L. We suggest assessing the efficiency using blood markers after six weeks of treatment. Trial registration no. EudraCT 2006-000478-56.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".