Observer reproducibility and validity of systems for clinical classification of angina pectoris: comparison with radionuclide imaging and coronary angiography
Bibliographic record
Abstract
OBJECTIVE: To assess reproducibility and validity of clinical classification of angina pectoris (AP) patients. DESIGN: Fifty-six patients scheduled for coronary angiography because of stable AP were classified by two independent observers with regard to (i) type and (ii) severity of chest pain (Canadian Cardiovascular Society, CCS) and (iii) cardiac functional status (New York Heart Association, NYHA). Myocardial perfusion imaging (MPI) was performed in 55 including measurement of ejection fraction in 46, angiography was undertaken in 51. RESULTS: Observers agreed 100% on the presence (n = 45) or absence (n = 11) of angina. They agreed in 52 (93%), 48 (86%), and 42 (75%) patients with regard to type of pain, CCS grade, and NYHA class, respectively. In the remaining patients, they disagreed by one class only. The positive and negative predictive values of typical/atypical angina for perfusion abnormalities and coronary disease were 55%/82% and 53%/ 82%, respectively. CONCLUSIONS: Observer agreement was excellent for presence, type, and severity of chest pain but moderate with regard NYHA class. Clinical judgment could not predict with reasonable accuracy abnormal perfusion or coronary artery disease.
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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 | 0.031 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".