Significance of the treadmill scores and high-risk criteria for exercise testing in non-high-risk patients with unstable angina and an intermediate Duke treadmill score
Bibliographic record
Abstract
BACKGROUND: The appropriate management of patients with an intermediate Duke treadmill score (DTS) is not well established.The aim of this study is to compare several treadmill indexes (American College of Cardiology/American Heart Association (ACC/AHA) High-Risk Criteria for exercise testing,Veterans Affairs and West Virginia Prognostic Score, ST/Heart Rate Index, Failure to attain 85% of age-predicted maximum Heart Rate) with ST-segment depression in detecting significant or severe coronary artery disease as determined by coronary angiography in patients with an intermediate DTS. METHODS: 144 consecutive patients admitted to the hospital for unstable angina were studied. RESULTS: The sensitivities of the ACC/AHA High-Risk Criteria and West Virginia Prognostic Score were greater than 95% for the detection of significant coronary artery disease and 96.67% for the detection of severe coronary artery disease. The sensitivity of I mm ST depression for the detection of significant and severe coronary disease was 74.74% and 86.67%, respectively. The combined evaluation of ST-segment depression > or =1 mm and exercise-induced angina could efficiently identify a population with a high prevalence of significant coronary artery disease (specificity of 95.92%, positive predictive value of 94.29%). CONCLUSIONS: The ACC/AHA High-Risk Criteria was West Virginia Prognostic Score provided relevant diagnostic information in patients with an intermediate DTS. A coronary angiography is to be recommended in patients with an intermediate DTS who also present ST-segment depression > or =1 mm and exercise-induced angina.
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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 | 0.001 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".