Iron Deficiency, Anemia, and Iron Supplementation in Patients With Heart Failure: A Population-Level Study
Bibliographic record
Abstract
BACKGROUND: Studies have shown an association between iron deficiency (ID) and clinical outcomes in patients with heart failure (HF), irrespective of the presence of ID anemia (IDA). The current study used population-level data from a large, single-payer health care system in Canada to investigate the epidemiology of ID and IDA in patients with acute HF and those with chronic HF, and the iron supplementation practices in these settings. METHODS: All adult patients with HF in Alberta between 2012 and 2019 were identified and categorized as acute or chronic HF. HF subtypes were determined through echocardiography data, and ID (serum ferritin concentration <100 μg/L, or ferritin concentration between 100 and 300 μg/L along with transferrin saturation <20%), and IDA through laboratory data. Broad eligibility for 3 clinical trials (AFFIRM-AHF [Study to Compare Ferric Carboxymaltose With Placebo in Patients With Acute HF and ID], IRONMAN [Intravenous Iron Treatment in Patients With Heart Failure and Iron Deficiency], and HEART-FID [Randomized Placebocontrolled Trial of Ferric Carboxymaltose as Treatment for HF With ID]) was determined. RESULTS: Among the 17 463 patients with acute HF, 38.5% had iron studies tested within 30 days post-index-HF episode (and 34.2% of the 11 320 patients with chronic HF). Among tested patients, 72.6% of the acute HF and 73.9% of the chronic HF were iron-deficient, and 51.4% and 49.0% had IDA, respectively. Iron therapy was provided to 41.8% and 40.5% of patients with IDA and acute or chronic HF, respectively. Of ID patients without anemia, 19.9% and 21.7% were prescribed iron therapy. The most common type of iron therapy was oral (28.1% of patients). Approximately half of the cohort was eligible for each of the AFFIRM-AHF, intravenous iron treatment in patients with HF and ID, and HEART-FID trials. CONCLUSIONS: Current practices for investigating and treating ID in patients with HF do not align with existing guideline recommendations. Considering the gap in care, innovative strategies to optimize iron therapy in patients with HF are required.
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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) | 0.000 | 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) | 0.000 | 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".