Abstract 175: Evaluation of 30-day Mortality in Patients With ST-Elevation Myocardial Infarction (STEMI) Across All Hospital Centers Performing Primary Percutaneous Coronary Intervention (PPCI) in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: PPCI is the predominant reperfusion treatment for STEMI in Quebec, Canada. Our systematic field evaluation, during a 6-month period in 2008-9, provided the opportunity to compare patient characteristics, processes of care and 30-day mortality across Quebec’s 13 PPCI centers. METHODS: All STEMI patients, who either presented directly or were transferred to one of these 13 PPCI centers, were included in the analyses. Patients transferred after fibrinolytic treatment were excluded. Since patient outcomes within the same hospital may be correlated, generalized estimating equation (GEE) models were used to compare 30-day mortality across centers, adjusting for patient-level risk factors (sex, TIMI index, anterior myocardial infarction, history of heart failure/shock) and for hospital-level characteristics. RESULTS: The majority of patients treated in the 13 PPCI centers were transferred for PPCI from non-tertiary centers (n=785, 62%), and these patients were unlikely to receive timely treatment (i.e., only 26% with first door-to-device time ≤90 min). Of the remaining 490 (38%) patients who presented directly to a PPCI center, 70% had timely treatment. Across the 13 PPCI centers, crude 30-day mortality varied widely (1.5% - 16.3%) and variation persisted after adjustment for patient risk factors (2.1% - 11.2%). STEMI volume per PPCI center and the presence of cardiac surgery on-site were not associated with 30-day mortality. In the final GEE model containing all patient factors considered and 3 hospital-level factors (proportion of patients treated with a radial approach, proportion of patients transferred for PPCI, proportion of patients with timely PPCI), the odds ratio for death decreased by 18% for every 20% increase in the proportion of patients treated with a radial approach, and decreased by 25% for every 20% increase in the proportion of patients with timely PPCI. Conversely, the odds ratio increased by 28% for every 20% increase in the proportion of transferred patients. CONCLUSION: Thirty-day STEMI mortality can vary substantially across PPCI centers within a complete system of care. Our findings suggest that 30-day STEMI mortality could be reduced if PPCI centers discouraged transfers with expected untimely delays.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".