Oral iron supplementation: Potential implications for the gut microbiome and metabolome in patients with CKD
Bibliographic record
Abstract
Patients with chronic kidney disease (CKD) and loss of kidney function are at increased risk for morbidity and mortality. The risks of CKD are attributed to "uremia," an increased concentration of uremic retention solutes (toxins) in the plasma. Recently, a colo-renal axis became clearly apparent and uremia has been associated with an altered gut microbiome composition and metabolism. There is a high prevalence of anemia in patients with CKD, for which patients are often treated with oral or intravenous iron. Recent in vivo and in vitro studies have reported adverse effects of oral iron supplementation on the gut microbiota composition, gut metabolome, and intestinal health, which in turn may result in an increased production of uremic toxins. It may also affect circulating levels of other microbe-derived molecules, that can act as mediators of immune regulation. Changes in body iron levels have also been reported to exert subtle effects on host immune function by modulating immune cell proliferation and differentiation, and by directly regulating cytokine formation and antimicrobial immune effector mechanisms. Based on the foregoing it is conceivable that oral iron supplementation in iron deficient predialysis CKD patients adversely changes gut microbiota composition, the gut and systemic metabolome, and host immunity and infection. Future studies are needed to confirm these hypotheses and to assess whether, compared to IV iron supplementation, oral iron supplementation negatively impacts on morbidity of CKD, and whether these adverse effects depend on the iron bioavailability of the iron formulation to the microbiota.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".