Intravenous iron therapy results in rapid and sustained rise in myocardial iron content through a novel pathway
Bibliographic record
Abstract
BACKGROUND AND AIMS: Intravenous iron therapies contain iron-carbohydrate complexes, designed to ensure iron becomes bioavailable via the intermediary of spleen and liver reticuloendothelial macrophages. How other tissues obtain and handle this iron remains unknown. This study addresses this question in the context of the heart. METHODS: A prospective observational study was conducted in 12 patients receiving ferric carboxymaltose (FCM) for iron deficiency. Myocardial, spleen, and liver magnetic resonance relaxation times and plasma iron markers were collected longitudinally. To examine the handling of iron taken up by the myocardium, intracellular labile iron pool (LIP) was imaged in FCM-treated mice and cells. RESULTS: In patients, myocardial relaxation time T1 dropped maximally 3 h post-FCM, remaining low 42 days later, while splenic T1 dropped maximally at 14 days, recovering by 42 days. In plasma, non-transferrin-bound iron (NTBI) peaked at 3 h, while ferritin peaked at 14 days. Changes in liver T1 diverged among patients. In mice, myocardial LIP rose 1 h and remained elevated 42 days after FCM. In cardiomyocytes, FCM exposure raised LIP rapidly. This was prevented by inhibitors of NTBI transporters T-type and L-type calcium channels and divalent metal transporter 1. CONCLUSIONS: Intravenous iron therapy with FCM delivers iron to the myocardium rapidly through NTBI transporters, independently of reticuloendothelial macrophages. This iron remains labile for weeks, reflecting the myocardium's limited iron storage capacity. These findings challenge current notions of how the heart obtains iron from these therapies and highlight the potential for long-term dosing to cause cumulative iron build-up in the heart.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 |
| 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".