P5557Association of anemia with in-hospital outcomes among ST-elevation myocardial infarction patients receiving primary percutaneous coronary intervention
Bibliographic record
Abstract
Background: Baseline anemia is believed to confer a poor prognosis among patients with acute coronary syndrome. However, relatively few data exist regarding the association of anemia with in-hospital outcomes, including bleeding, among ST-elevation myocardial infarction (STEMI) patients receiving primary percutaneous coronary intervention (pPCI). Purpose: This retrospective analysis explored the impact of admission hemoglobin levels on in-hospital outcomes among a contemporary STEMI cohort undergoing pPCI. Methods: We identified 1919 STEMI patients who underwent pPCI in two quaternary hospitals within the Vancouver Coastal Health Authority (2007–2016), of which 322 (16.8%) were anemic. Anemia was defined as a hemoglobin level <12 g/dL in women and <13 g/dL in men. Between-group differences in in-hospital outcomes, including heart failure, cardiogenic shock, major bleeding, and death were examined. Spearman correlation (rs) and multivariate logistic regression were used to evaluate the relationship of anemia with outcomes. Results: Compared to non-anemic patients, anemic patients were more likely to have hypertension, diabetes, and a prior MI, and were more likely to present with heart failure (9.4% vs 4.4%, p<0.001) and cardiogenic shock (12.6% vs 5.7%, p<0.001). Baseline anemia and lower hemoglobin were independently associated with major bleeding, but not all-cause mortality (Figure). There was no significant correlation between admission hemoglobin values (rs=0, p=0.9) or anemia with reperfusion times (OR 0.95; 95% CI 0.74 -1.22).
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".