Hypothetical ratings of coronary angiography appropriateness: are they associated with actual angiographic findings, mortality, and revascularisation rate? The ACRE study
Bibliographic record
Abstract
OBJECTIVE: To determine whether ratings of coronary angiography appropriateness derived by an expert panel on hypothetical patients are associated with actual angiographic findings, mortality, and subsequent revascularisation in the ACRE (appropriateness of coronary revascularisation) study. DESIGN: Population based, prospective study. The ACRE expert panel rated hypothetical clinical indications as inappropriate, uncertain, or appropriate before recruitment of a cohort of real patients. SETTING: Royal Hospitals Trust, London, UK. PARTICIPANTS: 3631 consecutive patients undergoing coronary angiography (no exclusion criteria). MAIN OUTCOME MEASURES: Angiographic findings, mortality (n = 226 deaths), and revascularisation (n = 1556 procedures) over 2.5 years of follow up. RESULTS: The indications for coronary angiography were rated appropriate in 2253 (62%) patients. 166 (5%) coronary angiograms were performed for indications rated inappropriate, largely for asymptomatic or atypical chest pain presentations. The remaining 1212 (33%) angiograms were rated uncertain, of which 47% were in patients with mild angina and no exercise ECG or in patients with unstable angina controlled by inpatient management. Three vessel disease was more likely among appropriate cases and normal coronaries were more likely among inappropriate cases (p < 0.001). Mortality and revascularisation rates were highest among patients with an appropriate indication, intermediate in those with an uncertain indication, and lowest in the inappropriate group (log rank p = 0.018 and p < 0.0001, respectively). CONCLUSION: The ACRE ratings of appropriateness for angiography predicted angiographic findings, mortality, and revascularisation rates. These findings support the clinical usefulness of expert panel methods in defining criteria for performing coronary angiography.
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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 | 0.009 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".