Time to treatment and the impact of a physician on prehospital management of acute ST elevation myocardial infarction: insights from the ASSENT-3 PLUS trial
Bibliographic record
Abstract
OBJECTIVES: To assess the impact of variation in prehospital care across distinct health care environments in ASSENT (assessment of the safety and efficacy of a new thrombolytic) -3 PLUS, a large (n = 1639) contemporary multicentred international trial of prehospital fibrinolysis. Specifically, the objectives were to assess predictors of time to treatment, whether components of time to treatment vary across countries, and the impact of physician presence before hospitalisation on time to treatment, adherence to protocol, and clinical events. METHODS: Patient characteristics associated with early treatment (< or = 2 hours), comparison of international variation in time to treatment, and components of delay were assessed. Trial specific patient data were linked with site specific survey responses. RESULTS: Younger age, slower heart rate, lower systolic blood pressure, and prior percutaneous coronary intervention were associated with early treatment. Country of origin accounted for the largest proportion of variation in time. Intercountry heterogeneity was shown in components of elapsed time to treatment. Physicians in the prehospital setting enrolled 63.8% of patients. The presence of a physician was associated with greater adherence to protocol mandated treatments and procedures but with delay in time to treatment (120 v 108 minutes, p < 0.001). CONCLUSION: Country of enrollment accounted for the largest proportion of variation in time to treatment and intercountry heterogeneity modulated components of delay. The effectiveness and safety of prehospital fibrinolysis was not influenced by the presence of a physician. These data, acquired in diverse health care environments, provide new understanding into the components of prehospital treatment delay and the opportunities to further reduce time to fibrinolysis for patients with ST elevation myocardial infarction.
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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 | 0.009 | 0.016 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".