Autologous bone marrow mononuclear stem cells for acute myocardial infarction: is it only about time?
Bibliographic record
Abstract
This editorial refers to ‘A randomized double-blind controlled study of early intracoronary autologous bone marrow cell infusion in acute myocardial infarction: the REGENERATE-AMI clinical trial’†, by F. Choudry et al., on page 256. In 2002, Strauer et al.1 reported the results of the first phase I study testing the safety of intracoronary (IC) administration of autologous bone marrow mononuclear stem cells (BMMSCs) for acute myocardial infarction (AMI). Since then, we have seen a series of trials using mixed cell types with heterogeneous designs in terms of both the number and the timing of BMMSCs administration that have yielded conflicting results2 (Figure 1). For example, Nowbar et al.3 found no beneficial effect on left ventricular ejection fraction (LVEF) when analysing BMMSCs trials without any discrepancies, while a meta-analysis by Afzal et al.4 (48 studies; 2602 patients) showed an improvement in both LVEF (+2.92%) and infarct size (−2.25%), as well as remodelling. Taken as a whole, these contradictory findings have left the general cardiology community somewhat indifferent and have arguably shrouded the field of BMMSC AMI research in a dark fog from which it has yet to emerge.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".