Age-related risk of major adverse cardiac event risk and coronary artery disease extent and severity by coronary CT angiography: results from 15 187 patients from the International Multisite CONFIRM Study
Bibliographic record
Abstract
AIMS: Prior studies evaluating the prognostic utility of cardiac CT angiography (CCTA) have been largely constrained to an all-cause mortality endpoint, with other cardiac endpoints generally not reported. To this end, we sought to determine the relationship of extent and severity of coronary artery disease (CAD) by CCTA to risk of incident major adverse cardiac events (MACEs) (defined as death, myocardial infarction, and late revascularization). METHODS AND RESULTS: We identified subjects without prior known CAD who underwent CCTA and were followed for MACE. CAD by CCTA was defined as none (0% luminal stenosis), mild (1-49% luminal stenosis), moderate (50-69% luminal stenosis), or severe (≥70% luminal stenosis), and ≥50% luminal stenosis was considered as obstructive. CAD severity was judged on per-patient, per-vessel, and per-segment basis. Time to MACE was estimated using univariable and multivariable Cox proportional hazards models. Among 15 187 patients (57 ± 12 years, 55% male), 595 MACE events (3.9%) occurred at a 2.4 ± 1.2 year follow-up. In multivariable analyses, an increased risk of MACE was observed for both non-obstructive [hazard ratio (HR) 2.43, P < 0.001] and obstructive CAD (HR: 11.21, P < 0.001) when compared with patients with normal CCTA. Risk-adjusted MACE increased in a dose-response relationship based on the number of vessels with obstructive CAD ≥50%, with increasing hazards observed for non-obstructive (HR: 2.54, P < 0.001), obstructive one-vessel (HR: 9.15, P < 0.001), two-vessel (HR: 15.00, P < 0.001), or three-vessel or left main (HR: 24.53, P < 0.001) CAD. Among patients stratified by age <65 vs. ≥65 years, older individuals experienced higher risk-adjusted hazards for MACE for non-obstructive, one-, and two-vessel, with similar event rates for three-vessel or left main (P < 0.001 for all) compared with normal individuals age <65. Finally, there was a dose relationship of CAD findings by CCTA and MACE event rates with each advancing decade of life. CONCLUSION: Among individuals without known CAD, non-obstructive, and obstructive CAD are associated with higher MACE rates, with different risk profiles based on age.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".