Influence of symptom typicality for predicting MACE in patients without obstructive coronary artery disease: From the CONFIRM Registry (Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry)
Bibliographic record
Abstract
Our objective was to assess the prognostic value of symptom typicality in patients without obstructive coronary artery disease (CAD), determined by coronary computed tomographic angiography (CCTA). We identified 4215 patients without prior history of CAD and without obstructive CAD (<50% CCTA stenosis). CAD severity was categorized as nonobstructive (1%-49%) and none (0%). Based upon the Diamond-Forrester criteria for angina pectoris, symptom typicality was classified as asymptomatic, nonanginal, atypical, and typical. Multivariable Cox proportional hazards models were used to assess the risk of major adverse cardiac events (MACE), comprising all-cause mortality, myocardial infarction, unstable angina, and late revascularization, according to symptom typicality. Mean patient age was 57.0 ±12.0 years (54.9% male). During a median follow-up of 5.3 years (interquartile range, 4.6-5.9 years), MACE were reported in 312 (7.4%) patients. Among patients with nonobstructive CAD, there was an association between symptom typicality and MACE (P for interaction = 0.05), driven by increased risk of MACE among those with typical angina and nonobstructive CAD (hazard ratio: 1.62, 95% confidence interval: 1.06-2.48, P = 0.03). No consistent relationship was found between symptom typicality and MACE among patients without any CAD (hazard ratio: 0.73, 95% confidence interval: 0.34-1.57, P = 0.08). In the CONFIRM registry, patients who presented with concomitant typical angina and nonobstructive CAD had a higher rate of MACE than did asymptomatic patients with nonobstructive CAD. However, the presence of typical angina did not appear to portend worse prognosis in patients with no CAD.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| 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".