Sustained elevation of serum CD40 ligand levels one month after coronary angioplasty predicts angiographic restenosis.
Bibliographic record
Abstract
BACKGROUND: Percutaneous coronary intervention induces an early inflammatory reaction. The intensity of such a reaction as measured by high-sensitivity C-reactive protein has been correlated with recurrent ischemic events, but its association with restenosis remains uncertain. OBJECTIVES: To characterize the type and duration of the postangioplasty inflammatory reaction and to identify new inflammatory markers correlating with restenosis. METHODS: Fifty-three consecutive patients who underwent successful balloon angioplasty were studied. Levels of specific inflammatory markers were measured before intervention, and at one-month and six-month follow-up. Six-month clinical and angiographic follow-up was conducted in all patients, and quantitative coronary analysis was systematically performed. RESULTS: Levels of soluble CD40 ligand (sCD40L) and matrix metalloproteinase-2 showed a rise and fall pattern over six months, with peak levels measured at one month (P < 0.0001), while levels of soluble vascular cell adhesion molecule-1 increased after angioplasty and remained elevated at six months (P = 0.07). Plasma levels of sCD40L at one month correlated with angiographic late loss (r = 0.48, P = 0.001) and were predictive of six-month restenosis (area under receiver operating characteristic curve 0.75 [95% CI 0.61 to 0.88]). CONCLUSIONS: The results imply that inflammation persists for at least one month following angioplasty and that future therapeutic interventions targeting inflammation to prevent restenosis should be active during this period. Furthermore, the ability of sCD40L levels to predict restenosis at six months may indicate the relevance of this pathway as a therapeutic target for restenosis prevention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".