Combined erythropoietin and iron therapy for anaemic patients undergoing transcatheter aortic valve implantation: the EPICURE randomised clinical trial
Bibliographic record
Abstract
AIMS: The aim of this study was to evaluate, in anaemic patients, the efficacy of erythropoietin (EPO) in reducing red cell (RC) transfusion rates post TAVI. METHODS AND RESULTS: This was a randomised double-blind trial. Patients with severe symptomatic aortic stenosis and concomitant anaemia with an indication for TAVI were randomised (1:1) to receive two weight-based doses of EPO (darbepoetin alfa)+iron or placebo at days 10 (±4 days) and 1 (±1 day) pre TAVI. The primary outcome was the rate of RC transfusions at 30 days. A total of 100 patients (mean age 81±7 years, male 49%) were included: 48 patients received EPO (+iron) and 52 patients received placebo. Baseline characteristics and procedural findings were well balanced between groups except for baseline haemoglobin levels, which were lower in those patients receiving EPO (10.7±1.2 vs. 11.3±1.1 g/dl, p=0.01). The rate of 30-day RC transfusion was similar in both groups (27.1 vs. 25.0% in the EPO and placebo groups, respectively; adjusted odds ratio 1.05, 95% CI: 0.42-2.64, p=0.92), and no differences were observed in the number of RC units per transfused patient (1 [1-3] vs. 2 [1-2] in the EPO and placebo groups, respectively, adjusted p=0.99). Rates of 30-day mortality, stroke, new-onset atrial fibrillation, acute kidney injury, and troponin peak were also similar between groups (p>0.20 for all). CONCLUSIONS: EPO (+iron) administration failed to reduce RC transfusion rates or the per-patient number of transfusion units in anaemic patients undergoing TAVI.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".