Effect of Platelet GPIIb/IIIa Receptor Blockade With MK383 on Infarct Size and Myocardial Blood Flow in a Canine Reocclusion Model
Bibliographic record
Abstract
Platelet activation and aggregation during ischemia influence reperfusion-related myocyte necrosis, myocardial perfusion at the microvascular level, and thereby eventual recovery of cardiac performance. Inhibition of platelet activity therefore represents a worthwhile target to reduce cellular injury. The current study examined the effects of MK383 (tirofiban), a potent inhibitor of platelet aggregation, on infarct size and myocardial perfusion in canine subjects to either reocclusion (ie, 120-minute + 60-minute ischemia with intervening reperfusion) or prolonged occlusion (ie, 3 hours) followed by reperfusion (180 minutes). Platelet aggregation, infarct size (tetrazolium staining), coronary blood flow (flow probe), coronary vascular reserve, and myocardial perfusion (microspheres) were evaluated. MK383, administered at the time of reperfusion, produced a modest reduction of tissue necrosis (compared to saline-treated controls) in the reocclusion and prolonged occlusion studies. Blood flow in the infarct-related artery after coronary occlusion was comparable between treatment groups, as was myocardial perfusion in the deeper layers of the ischemic region; coronary vascular reserve decreased progressively during reperfusion. Of note, compensatory changes in blood flow within the adjacent nonischemic myocardium were not observed. In conclusion, we report that that limiting platelet aggregation during reperfusion impacted infarct development. Continued investigation into the mechanisms by which inhibition of platelet activity protects myocardium against ischemia-reperfusion injury and improves clinical outcomes is necessary.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| 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".