Reperfusion times for ST elevation myocardial infarction: a prospective audit
Bibliographic record
Abstract
BACKGROUND: New published guidelines recommend treatment of ST elevation myocardial infarction (STEMI) within 30 minutes of first medical contact to thrombolysis and 90 minutes to primary percutaneous coronary intervention (PCI). OBJECTIVES: To determine how a tertiary care center compares to these new guidelines and to evaluate the success of measures directed to shorten delays. METHODS: This was a prospectively designed audit loop using retrospective chart review. Specific time intervals were evaluated: 1) T2 (ER presentation to diagnostic EKG; 2) T ER (ER presentation to reperfusion); and 3) T AHA (first medical contact to reperfusion). Results of the initial 12-month data were conveyed to Emergency Room staff and a dedicated EKG machine was placed in the ER for the subsequent 12 months, and the results were then re-analyzed. RESULTS: In 2003-4, 58 patients with STEMI were identified, with 41 (70.7%) receiving reperfusion. Of those receiving thrombolysis, median T AHA was 54 [37-72] minutes, with 12.0%<30 minutes, while those receiving PCI, median T AHA was 58 [43-78] minutes, with 25.0%<90 minutes. In 2004-5, 52 patients had STEMI, with 40 (76.9%) receiving reperfusion. The percentage of patients meeting the guidelines was 14.3% for the thrombolysis group and 11.1% for the PCI group. Introduction of a dedicated EKG machine led to a strong trend towards improvement in median T2 (22 vs 10 minutes; P=0.07), but other treatment times remained unchanged. CONCLUSIONS: Treatment times are longer than recommended guidelines. More comprehensive strategies and improved coordination of medical services are required to shorten pre-contact and post-contact response times.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".