Intervention in acute coronary syndromes: do patients undergo intervention on the basis of their risk characteristics? The Global Registry of Acute Coronary Events (GRACE)
Bibliographic record
Abstract
OBJECTIVE: To determine whether revascularisation is more likely to be performed in higher-risk patients and whether the findings are influenced by hospitals adopting more or less aggressive revascularisation strategies. METHODS: GRACE (Global Registry of Acute Coronary Events) is a multinational, observational cohort study. This study involved 24,189 patients enrolled at 73 hospitals with on-site angiographic facilities. RESULTS: Overall, 32.5% of patients with a non-ST elevation acute coronary syndrome (ACS) underwent percutaneous coronary intervention (PCI; 53.7% in ST segment elevation myocardial infarction (STEMI)) and 7.2% underwent coronary artery bypass grafting (CABG; 4.0% in STEMI). The cumulative rate of in-hospital death rose correspondingly with the GRACE risk score (variables: age, Killip class, systolic blood pressure, ST segment deviation, cardiac arrest at admission, serum creatinine, raised cardiac markers, heart rate), from 1.2% in low-risk to 3.3% in medium-risk and 13.0% in high-risk patients (c statistic = 0.83). PCI procedures were more likely to be performed in low- (40% non-STEMI, 60% STEMI) than medium- (35%, 54%) or high-risk patients (25%, 41%). No such gradient was apparent for patients undergoing CABG. These findings were seen in STEMI and non-ST elevation ACS, in all geographical regions and irrespective of whether hospitals adopted low (4.2-33.7%, n = 7210 observations), medium (35.7-51.4%, n = 7913 observations) or high rates (52.6-77.0%, n = 8942 observations) of intervention. CONCLUSIONS: A risk-averse strategy to angiography appears to be widely adopted. Proceeding to PCI relates to referral practice and angiographic findings rather than the patient's risk status. Systematic and accurate risk stratification may allow higher-risk patients to be selected for revascularisation procedures, in contrast to current international practice.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".