Comparative Study of Ferrous Fumarate, Ferrous Ascorbate, and Polysaccharide Iron for Treating Iron Deficiency Anemia in Adults
Bibliographic record
Abstract
Iron deficiency anemia (IDA) is a highly prevalent condition encountered in clinical practice and represents a major global health concern, affecting an estimated 1.92 billion individuals worldwide. Despite its prevalence and the availability of various oral iron formulations with wide cost variations, comparative data on their efficacy and tolerability remain limited. This randomized, open-label trial conducted across two centres evaluated the efficacy, tolerability, and adherence of three oral iron supplements in improving hemoglobin and ferritin levels in adults with IDA. The study compared ferrous fumarate (Eurofer, 100 mg elemental iron, $15.87 for 90 tablets), ferrous ascorbate (EBMfer, 100 mg elemental iron, $68.97 for 90 tablets), and polysaccharide iron (FeraMAX, 150 mg elemental iron, $77.97 for 90 tablets). A total of 111 participants aged ≥18 years were randomly assigned into one of three treatment groups and monitored over a 12-week period. Both ferrous fumarate (p=0.001) and ferrous ascorbate (p<0.001) demonstrated significantly greater hemoglobin and ferritin levels compared to polysaccharide iron. Specifically, ferrous fumarate led to mean increases in hemoglobin and ferritin of 11.59 g/L (95% confidence interval [CI]: 7.87–15.3, standard deviation [SD]: 10.7) and 19.21 µg/L (95% CI: 7.82–28.6, SD: 29.8), respectively. Ferrous ascorbate showed mean increases in hemoglobin and ferritin levels of 17.14 g/L (95% CI: 13.5–20.8, SD: 10.7) and 23.51 µg/L (95% CI: 16.5–30.5, SD: 20.3), respectively. Polysaccharide iron showed mean increases in hemoglobin and ferritin of 3.56 g/L (95% CI: -0.06–7.18, SD: 10.4) and 3.21 µg/L (95% CI: -0.07–6.48, SD: 9.39), respectively. Adverse events occurred more frequently with ferrous fumarate (13 events) compared with ferrous ascorbate (8 events) and polysaccharide iron (6 events). The most commonly reported side effects across all groups were constipation and bloating, well-documented side effects of iron supplements. These findings demonstrate that ferrous fumarate and ferrous ascorbate significantly outperformed polysaccharide iron in improving hemoglobin and ferritin levels. Given its lower cost and comparable efficacy, ferrous fumarate may be the most cost-effective option and warrants consideration in updates to Canadian treatment guidelines.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".