A cohort study of circulating progenitor cells after ST-segment elevation and non-ST segment elevation myocardial infarction in non-diabetic and diabetic patients
Bibliographic record
Abstract
Background Myocardial infarction induces elevation of progenitor cells in the circulation, a reparative response inhibited by type-2 diabetes. Objectives Determine if myocardial infarct severity and diabetes interactively influence the migratory activity of CD34+/CXCR4+ progenitor cells and if the migratory test predicts cardiac outcomes. Materials and methods A longitudinal study was conducted on patients with or without diabetes with a STEMI or NSTEMI. CD34+/CXCR4+ cells were measured in the peripheral blood using flow cytometry, and migratory activity was tested in vitro on cells isolated from samples collected on days 0 and 4 post-infarct. Cardiac function was assessed at three months using cardiac MRI. Results Of 1,149 patients screened, 71 (6.3%) were eligible and consented. Fifty had STEMI (16 with diabetes) and 21 NSTEMI (8 with diabetes). The proportion of CD34+/CXCR4+ cells within blood mononuclear cells was 1.96 times higher after STEMI compared with NSTEMI (GMR = 1.96, 95% CI 0.87, 4.37) and 1.55 times higher in patients with diabetes compared to patients without diabetes (GMR = 1.55, 95% CI 0.77, 3.13). In the latter, STEMI was associated with a 2.42-times higher proportion of migrated CD34 + /CXCR4 + cells compared with NSTEMI (GMR = 2.42, 95% CI 0.66, 8.81). In patients with diabetes, the association was the opposite, with a 55% reduction in the proportion of migrated CD34+/CXCR4+ cells. No statistically significant associations were observed between the frequency in peripheral blood or in vitro migration capacity of CD34+/CXCR4+ cells and MRI outcomes. Conclusion We document the interaction between infarct and diabetes on the migratory activity of CD34+/CXCR4+ cells. The test did not predict functional outcomes in the studied cohort.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".