Aspiration thrombectomy in ST-elevation myocardial infarction
Bibliographic record
Abstract
The major challenge in the treatment of ST-elevation myocardial infarction (STEMI) is not only restoration of normal coronary blood flow but also microvascular perfusion. In fact, both electrocardiographic (ST segment resolution) and angiographic measures of myocardial perfusion (myocardial blush grade) have been shown to predict mortality after primary percutaneous coronary intervention (PPCI). Initial enthusiasm for manual thrombectomy arose after the apparent mortality benefit observed in the TAPAS trial (N=1,071). Meta-analyses of small trials suggest that manual thrombectomy improves epicardial and microvascular perfusion with trends towards benefit for survival. On the other hand, meta-analyses of small trials of mechanical thrombectomy show improvement in ST resolution without an effect on survival. Recently, the TASTE trial (N=7,244) showed no reduction in mortality with manual thrombectomy but trends toward reduction in rates of rehospitalisation for recurrent MI and stent thrombosis. The interpretation of TASTE should be cautious given that the trial had a much lower than expected mortality, and modest but important treatment effects cannot be excluded (20-30%). The largest trial, the ongoing TOTAL trial (N=10,700), will help determine the effect of manual thrombectomy for important clinical outcomes. A planned individual patient meta-analysis of the TOTAL and TASTE trials will have approximately 17,000 patients to examine the effect on clinical outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".