Relationship between elevated platelet volume and saphenous vein graft disease
Bibliographic record
Abstract
BACKGROUND: Saphenous vein graft (SVG) disease is the major determinant of long term graft viability in patients undergoing coronary artery bypass graft (CABG) surgery. Although, platelets play a major role in this pathogenetic process the nature of this interaction has not been yet been clarified. Mean platelet volume (MPV) reflects platelet production rate and stimulation. This study was designed to investigate MPV in patients with late stage SVG disease. METHODS: The study population composed of 188 patients who underwent elective coronary angiography more than one year after coronary artery bypass surgery. The study population was divided in to two groups according to SVG patency. The first group consisted of 90 patients (75 men, 15 women; mean age, 63.4 +/- 9.2 years) with patent SVG's (no-stenosis group). The second group consisted of 98 patients (80 men, 18 women; mean age, 62.1 +/- 10.1 years) with SVG stenosis based on the results of coronary angiography (stenosis group). Greater than 50% stenosis within the SVG was accepted as hemodynamically significant. RESULTS: MPV were significantly higher in patients with SVG disease in comparison with the patients without graft disease group (9.3 +/- 1.19 vs. 8.3 +/- 1.10 fl, respectively, p < 0.001). In a multiple regression model, SVG disease was independently associated with MPV (beta=0.837, p=0.05) along with LDL-cholesterol (beta=0.159, p=0.008) and time interval after bypass surgery (beta=-0.092, p=0.05). CONCLUSION: Platelet volume, and therefore platelet activation, appears to play a causal role in late SVG disease graft disease; hence, MPV may be useful as a post-operative marker of graft success.
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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 | 0.000 | 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) | 0.002 | 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".