Is coronary angiography performed in the appropriate patients after acute myocardial infarction?
Bibliographic record
Abstract
OBJECTIVE: Rates of coronary angiography (CA) after myocardial infarction (MI) vary widely between institutions. Furthermore, the indications for CA are often in conflict with recognized guidelines. The present study sought to determine the characteristics and the one-year mortality in patients with MI, regardless of age and hospital facilities, according to the use of CA after MI. METHODS AND RESULTS: Data were prospectively collected in all patients with MI admitted to all hospitals in three departments in the Rhône-Alpes region. Among 2493 patients, 1117 (45%) underwent CA. In multivariate analysis, CA rate was lower with increasing age, female sex, in patients with comorbidity or heart failure. CA was performed in 49% of patients admitted to hospitals with on-site CA vs. 32% in hospitals without on-site CA (OR: 3.54, after adjustment for patients' characteristics). One-year mortality rate was 6.5% for the CA group and 36.9% for the no-CA group. In multivariate analysis, age, history of angina pectoris, presence of Q waves, Killip class at admission II, III, or IV and CPK ratio > or = 9 were significant predictors of a higher one-year mortality, but performance of CA did not significantly influence it: RR: 0.79 (95% CI 0.58 to 1.07). CONCLUSIONS: Among patients with MI in a large unselected cohort in a French region, the one-year mortality was significantly lower in those referred for angiography. However, after correction for the confounding effects of simple baseline clinical indicators of risk, this apparent benefit reflected the fact that angiography was performed in those at lowest risk.
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 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".