P23 Inter-observer variability of coronary stenosis characterized by coronary angiography: a single-centre retrospective chart review by staff cardiologists
Bibliographic record
Abstract
Local practice varies considerably in criteria used to assess critical stenosis in coronary angiography. In this retrospective observational cohort, we examined the inter- and intra-rater reliability of visual interpretation of coronary arteriography. We assessed the impact of this inter-observer variability of coronary lesions on clinical decision-making with independent, blinded review of angiogram clips by three experienced interventional cardiologists including the original operator. A review of 200 angiograms performed at the Toronto General Hospital (TGH) showed a mean agreement between all participating observers (mean ICC) of 77.4 (i.e., an interobserver variability of 22.6%). The interobserver variability in proximal parts of the main coronary vessels was shown to be the lowest (i.e., highest agreement), while the midportion parts was the highest (i.e., lowest agreement) and the intermediate results were achieved in the distal parts. This analysis re-demonstrates the variability in visual interpretation of coronary angiograms and highlights the importance of considering augmenting visual interpretation with more objective measures in cases of clinical uncertainty.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".