Advanced Glycation End Products:Receptors for Advanced Glycation End Products Axis in Coronary Stent Restenosis: A Prospective Study
Bibliographic record
Abstract
This study was aimed to correlate the pre- and 6-month postpercutaneous coronary intervention (PCI) serum concentrations of advanced glycation end products (AGE), soluble receptors for advanced glycation end products (sRAGE), AGE/sRAGE ratio, and serum malondialdehyde (MDA) levels with in-stent restenosis (ISR) among patients receiving either a drug-eluting stent (DES) or a bare-metal stent (BMS).In-stent restenosis remains as an adverse outcome following PCI. Sixty consecutive nondiabetic, Caucasian male patients, diagnosed with a non-ST-elevation myocardial infarction who received either a DES or BMS via PCI, were enrolled. Baseline levels of serum AGE, sRAGE, AGE/sRAGE ratios, MDA, and angiographic parameters were determined at stenting and at 6 months. Patients with and without ISR at 6 months were compared on both baseline and 6-month biomarker levels and within stent types.The pre-PCI serum AGE levels and AGE/sRAGE ratios were higher in ISR patients compared with non-ISR patients, while the pre-PCI and post-PCI serum sRAGE levels were lower in ISR patients compared with non-ISR patients. The pre and post-PCI levels of MDA were also higher in ISR patients. Comparing stent types, relative levels of MDA between those with and without ISR at the respective time points were similar, although changes between time points appeared type specific.Post-PCI ISR correlates with low serum values of sRAGE and high serum values of AGE, MDA, and AGE/sRAGE ratio which are present at stenting. The associations of baseline AGE, sRAGE, AGE/sRAGE, and MDA levels with ISR appear consistent between stent types.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".