Association of pre‐hospital time intervals and clinical outcomes in ST‐elevation myocardial infarction patients
Bibliographic record
Abstract
Study Objectives: Timely coronary reperfusion is critical for favorable outcomes after ST-elevation myocardial infarction (STEMI). A substantial proportion of the total ischemic time is patient related, occurring before first medical contact (FMC). We aimed to expand the limited current understanding of the associations between prehospital intervals and clinical outcomes. Methods: We conducted a retrospective analysis of consecutive STEMI patients who underwent primary percutaneous coronary intervention (pPCI) (January 2009-March 2016) and assessed the associations between prehospital intervals and the incidence of new heart failure, cardiogenic shock, and hospital length of stay (LOS), adjusting for important clinical variables. Results: A total of 773 patients (77% men, median age 65 years) met eligibility criteria. The median pre-911 activation interval was 29 minutes (interquartile range: 11, 89); the median 911 call to FMC interval was 12 minutes (interquartile range: 9, 15). In multivariable analysis, there was a V-shaped relationship between the pre-911 activation interval and outcomes: a lower likelihood of new heart failure (odds ratio [OR] 0.51; 95% confidence interval [CI]: 0.30, 0.87), cardiogenic shock (OR 0.40; 95% CI: 0.21, 0.75) and prolonged LOS (OR 0.24; 95% CI: 0.14, 0.42) for midrange intervals (11-88 minutes) when compared to the early (< 11-minute) interval. There was no statistically significant relationship between total pre-FMC time and FMC to device activation time. Conclusions: Among ambulance-transported STEMI patients receiving pPCI, the shortest and longest pre-911 activation time intervals were associated with poorer outcomes. However, variation in post-FMC interval alone was not associated with outcomes, suggesting that interventions to reduce pre-FMC intervals must be prioritized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".