Electrical effects of stem cell transplantation for ischaemic cardiomyopathy: friend or foe?
Bibliographic record
Abstract
Despite advances in other realms of cardiac care, the mortality attributable to ischaemic cardiomyopathy has only marginally decreased over the last 10 years. These findings highlight the growing realization that current pharmacological and device therapies rarely reverse disease progression and rationalize a focus on novel means to reverse, repair and re-vascularize damaged hearts. As such, multiple candidate cell types have been used to regenerate damaged hearts either directly (through differentiation to form new tissue) or indirectly (via paracrine effects). Emerging literature suggests that robust engraftment of electrophysiolgically heterogeneous tissue from transplanted cells comes at the cost of a high incidence of ventricular arrhythmias. Similar electrophysiological studies of haematological stem cells raised early concerns that transplant of depolarized, inexcitable cells that also induce paracrine-mediated electrophysiological remodelling may be pro-arrhythmic. However, meta-analyses suggest that patients receiving haematological stem cells paradoxically may experience a decrease in ventricular arrhythmias, an observation potentially related to the extremely poor long-term survival of injected cells. Finally, early clinical and preclinical data from technologies capable of differentiating to a mature cardiomyocyte phenotype (such as cardiac-derived stem cells) suggests that these cells are not pro-arrhythmic although they too lack robust long-term engraftment. These results highlight the growing understanding that as next generation cell therapies are developed, emphasis should also be placed on understanding possible anti-arrhythmic contributions of transplanted cells while vigilance is needed to predict and treat the inadvertent effects of regenerative cell therapies on the electrophysiological stability of the ischaemic cardiomyopathic heart.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".