The impact of time to thrombolytic treatment on outcome in patients with acute myocardial infarction
Bibliographic record
Abstract
OBJECTIVES: To examine the impact of time to thrombolytic treatment on multiple acute outcome variables in a single trial of thrombolysis in acute myocardial infarction. DESIGN AND PATIENTS: Mortality and reinfarction rate were measured in 2770 patients with acute myocardial infarction who received thrombolysis within 12 hours in CORE, an international, dose ranging trial of poloxamer 188. Tc-99m sestamibi infarct size and radionuclide angiographic ejection fraction substudies included 1099 and 1074 patients, respectively. RESULTS: Time to thrombolysis, subgrouped by intervals (< 2, 2-4, > or = 4-6, and > or = 6 hours), was significantly associated with infarct size (median 15.0%, 18.5%, 22.0%, 18.5% of left ventricle; p = 0.033), mean (SD) ejection fraction (51.5 (12.0)%, 48. 3 (13.9)%, 48.2 (13.3)%, 48.2 (15.0)%; p = 0.006), 35 day mortality (5.7%, 7.1%, 7.9%, 12.5%; p = 0.0004), six month mortality (7.3%, 8. 6%, 10.4%, 15.5%; p < 0.0001), and 35 day reinfarction rate (6.1%, 3. 2%, 4.0%, 0.9%; p = 0.0001). CONCLUSIONS: In this single large trial, the beneficial effect of time to thrombolysis on infarct size and ejection fraction was restricted to treatment given within two hours of symptom onset, while the effect on mortality was evident over all time intervals. Reinfarction rate was higher in patients treated with earlier thrombolysis.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".