Impact of intracoronary injection of CD133+ bone marrow stem cells on coronary atherosclerotic progression in patients with STEMI
Bibliographic record
Abstract
OBJECTIVES: Adverse effects of intracoronary injection of stem cells on in-stent restenosis and atherosclerotic progression remain unclear. We sought to evaluate the adverse effects of intracoronary injection of CD133 cells on in-stent restenosis and atherosclerotic progression in the infarct-related and contralateral arteries using serial intravascular ultrasound (IVUS) analysis. METHODS: Baseline and 4-month follow-up IVUS images were obtained from 17 patients treated with intracoronary stem cell injection and 20 placebo patients after primary percutaneous coronary intervention in the COMPARE-AMI trial. In the infarct-related artery, the stented segment, 5 mm proximal and distal reference segments, and proximal and distal nonstented segments were analyzed every 1 mm; the entire segment of a contralateral artery was also analyzed every 1 mm. RESULTS: In the infarct-related artery analysis, the median percentage of in-stent neointimal hyperplasia (12.1 vs. 7.6%, P=0.95), the reduction in the minimum lumen area (MLA; -1.6 vs. -1.5 mm(2), P=0.97), and the MLA at follow-up (4.3 vs. 5.3 mm(2), P=0.21) were found to be similar between the stem cell and placebo groups. Changes in proximal and distal nonstented segment lumen areas and plaque burden were also similar between the stem cell and placebo groups; however, there was a decrease in the maximum arc of the attenuated plaque behind the stent from baseline to follow-up in the placebo group (P=0.004), but not in the stem cell group. In the contralateral artery, there were no differences in changes in MLA, plaque burden, or attenuated plaque between stem cell and placebo patients. CONCLUSION: Intracoronary injection of CD133(+) bone marrow stem cells has no IVUS-detectable effect on neointimal hyperplasia or atherosclerosis progression in either infarct-related or contralateral arteries.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".