Impact of ischaemic aetiology on the efficacy of intravenous ferric carboxymaltose in patients with iron deficiency and acute heart failure: insights from the AFFIRM‐AHF trial
Bibliographic record
Abstract
Aims In AFFIRM‐AHF, intravenous ferric carboxymaltose (FCM) reduced heart failure (HF) hospitalisations and improved quality of life versus placebo in iron‐deficient patients stabilised after an acute HF episode. This analysis explored the effects of FCM versus placebo in patients with ischaemic and non‐ischaemic HF aetiology. Methods and results We included 1082 patients from AFFIRM‐AHF: 590 with ischaemic HF (defined as investigator‐reported ischaemic HF aetiology and/or prior acute myocardial infarction and/or prior coronary revascularisation) and 492 with non‐ischaemic HF. The prevalences of male sex, comorbidities, and history of HF were higher in the ischaemic versus non‐ischaemic HF subgroup. Annualised event rates for the primary composite outcome of total HF hospitalisations and cardiovascular death with FCM versus placebo were 65.3 versus 100.6 per 100 patient‐years in the ischaemic HF subgroup (rate ratio [RR] 0.65, 95% confidence interval [CI] 0.47–0.89, p = 0.007) and 58.3 versus 52.5 in the non‐ischaemic HF subgroup (RR 1.11, 95% CI 0.75–1.66, p = 0.60) ( p interaction = 0.039). An interaction between HF aetiology and treatment effect was also observed for the secondary outcome of total HF hospitalisations ( p interaction = 0.038). A nominal increase in quality of life, assessed using the 12‐item Kansas City Cardiomyopathy Questionnaire, was observed with FCM versus placebo, within each subgroup. Conclusions Heart failure hospitalisations and cardiovascular deaths occurred at a higher rate in patients with ishaemic versus those with non‐ischaemic HF and were reduced by FCM versus placebo only in ischaemic patients. Further studies are needed to assess the role of aetiology in FCM efficacy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".