Bone Marrow Stem Cell Transplantation and Coronary Artery Bypass Grafting Surgery for Chronic Ischemic Myocardiopathy
Bibliographic record
Abstract
We studied 12 consecutive patients with chronic ischemic myocardiopathy treated with bone marrow adult stem cell (ASC) transplantation and coronary artery bypass grafting (CABG). The aim of the study was to evaluate functional class (New York Heart Association), wall motion score index (WMSI), and ejection fraction by echocardiography and to evaluate myocardial perfusion by single-photon emission computed tomography (SPECT). Follow-up evaluations were performed at 3, 6, and 12 months. The results revealed functional class improvement until 12 months, a progressive increase in the ejection fraction of 15% to 20% in the first 6 months, and a progressive increase in the WMSI by 35% to 45% in 12 months. Evaluation of the WMSI in the stem cell and CABG areas separately revealed a similar improvement in the first 3 months and a better progression in the CABG area. SPECT images revealed perfusion improvements in ischemic areas and no difference in fibrous tissue areas. These preliminary results show the safety of the method and its reproducibility. When performed concomitantly with CABG, bone marrow ASC transplantation may improve functional class, ejection fraction, WMSI, and myocardial perfusion. This study will be completed with all patients followed up for 12 months and compared with a control group.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".