Relationship Between Duke Treadmill Score and Coronary Artery Lesion Complexity
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to investigate the relationship between the Duke Treadmil Score (DTS) and coronary artery disease (CAD) complexity in patients with suspected coronary artery disease (CAD). METHODS: Sixty five patients who had positive exercise testing for CAD were enrolled. Coronary angiography was performed and Syntax score (SxScore), a marker of CAD complexity, was determined. The relationship between DTC and SxScore then evaluated. RESULTS: There was a strong negative correlation between DTS and SxScore (r = - 0.91, p < 0.001). In addition, patients with higher and intermediate risk as evaluated by DTS had increased SxScore compare to those that were low risk (23 ± 6, 6 ± 5 and 0 ± 0 respectively). CONCLUSIONS: A strong negative correlation was seen between DTS and coronary lesion complexity. By assessing DTS important information about coronary artery lesion complexity can be obtained before invasive 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".