Interventional Strategies in Thrombus Management for ST Elevation Myocardial Infarction
Bibliographic record
Abstract
The major limitation of modern primary percutaneous coronary intervention (PPCI) is distal embolisation of thrombus and microvascular obstruction. Microvascular flow, as measured by myocardial blush grade (MPG), predicts mortality after PPCI. Despite initial enthusiasm, current evidence does not support routine use of Intracoronary over intravenous glycoprotein 2b3a inhibitors during PPCI for ST elevation myocardial infarction (STEMI) to improve clinical outcomes. Manual thrombectomy (MT) improves MPG and reduces distal embolisation in meta-analyses of small trials. A single-centre trial (N=1071), the Thrombus aspiration during percutaneous coronary intervention in acute myocardial infarction study (TAPAS) trial showed a mortality reduction, which led guidelines to recommend routine manual aspiration. However, the largest randomised trial (Thrombus aspiration in ST-elevation myocardial infarction in Scandinavia [TASTE] trial, N=7021) showed no difference in mortality and only trends towards reduction in myocardial infarction (MI) and stent thrombosis. The TASTE trial had much lower than expected mortality and so was likely underpowered for modest but important treatment effects (20-30 % RRR). The Thrombectomy with PCI versus PCI alone in patients with STEMI undergoing primary PCI (TOTAL) trial (N=10,700) will determine if MT reduces important clinical events during PPCI. Thrombus management remains an important area of research in STEMI.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".