The Use of Hematopoietic Stem Cells for Heart Failure: A Systematic Review
Bibliographic record
Abstract
The purpose of this review is to summarize the current understanding of the therapeutic effect of stem cell-based therapies, including hematopoietic stem cells, for the treatment of ischemic heart damage. Following PRISMA guidelines, we conducted electronic searches in MEDLINE, and EMBASE. We screened 592 studies, and included RCTs, observational studies, and cohort studies that examined the effect of hematopoietic stem cell therapy in adult patients with heart failure. Studies that involved pediatric patients, mesenchymal stem cell therapy, and non-heart failure (HF) studies were excluded from our review. Out of the 592 studies, 7 studies met our inclusion criteria. Overall, administration of hematopoietic stem cells (via intracoronary or myocardial infarct) led to positive cardiac outcomes such as improvements in pathological left-ventricular remodeling, perfusion following acute myocardial infarction, and NYHA symptom class. Additionally, combined death, rehospitalization for heart failure, and infarction were significantly lower in patients treated with bone marrow-derived hematopoietic stem cells. Our review demonstrates that hematopoietic stem cell administration can lead to positive cardiac outcomes for HF patients. Future studies should aim to increase female representation and non-ischemic HF patients.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".