3100Diamond and Forrester-predicted vs. coronary CTA-observed prevalence of obstructive CAD in patients with stable chest pain: results from the PROMISE trial
Bibliographic record
Abstract
Background: Nearly 40 years ago Diamond and Forrester (DF) established a set of Pretest Probabilities (PTP) for obstructive coronary artery disease (CAD) based on populations referred to invasive coronary angiography. The Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial represents a unique opportunity to reevaluate these PTP in a large contemporary North American population of stable chest pain patients referred for noninvasive testing based on coronary CT angiography (CTA). Purpose: To compare PTP of obstructive CAD (CAD≥50%) based on DF stratification with the observed prevalence of CAD≥50%, as determined by standardized highly accurate expert core lab reads based on coronary CTA. Methods: We included participants enrolled in the PROMISE trial who were randomized to and received coronary CTA as a primary test. PTP for CAD≥50% were calculated based on the original DF as well as using the modified PTP (European Society of Cardiology (ESC)). The observed prevalence of CAD≥50% was assessed by six level III readers using a structured report from blinded to clinical care and outcomes. We compared predicted and observed prevalence of CAD≥50%.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".