Trends in acute reperfusion therapy for ST-segment elevation myocardial infarction from 1999 to 2006: we are getting better but we have got a long way to go
Bibliographic record
Abstract
AIM: Many patients who are eligible for acute reperfusion therapy receive it after substantial delays or not at all. We wanted to determine whether over the years more patients are receiving reperfusion therapy. METHODS AND RESULTS: This analysis is based on 10 954 patients with ST elevation or left bundle-branch block presenting within 12 h of symptom onset and enrolled in the GRACE registry between April 1999 and June 2006. Over this time, there was an increasing trend in use of primary percutaneous coronary intervention (PCI) from 15% to 44% (P < 0.001), while use of fibrinolytic therapy decreased (from 41 to 16%; P < 0.01). No trend in median time to primary PCI was seen but that for fibrinolysis declined significantly (from 40 to 34%; P < 0.0001). Hospital mortality declined (6.9-5.4%; P < 0.01); the relationship between observed and expected mortality improved over time (P = 0.06). Nevertheless, 33% of patients still received no reperfusion therapy. Factors associated with reperfusion use included age; prior myocardial infarction, heart failure or coronary artery bypass graft surgery; history of diabetes; female sex; and delay from symptom onset to hospital arrival. In 2006, 52% of patients receiving fibrinolysis had door-to-needle times >30 min and 42% of those undergoing primary PCI had door-to-balloon times >90 min. CONCLUSION: Primary PCI is now used much more than fibrinolysis. Although hospital mortality and delays to fibrinolytic reperfusion have improved, over 40% of patients reperfused still receive it outside the time window recommended, and one-third of potentially eligible patients receive no reperfusion.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".