P2487Long term prognostic utility of CT Coronary Angiography (CTCA) in older populations
Bibliographic record
Abstract
Background: The long-term prognostic value of CTCA-identified coronary artery disease (CAD) has not been validated in elderly patients (≥70yrs). We compared the ability of coronary CTCA to predict 5-year mortality in older vs. younger populations. Methods: From the prospective CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry, we analysed CTCA results according to age <70yrs (n=7,198, 57% male) vs. ≥70yrs (n=1,786, 46% male). The severity of CAD was classified according to maximal stenosis degree per vessel as none (0%), non-obstructive (1–49%) or obstructive (>50%). Cox-proportional hazard models assessed the relationship between CTCA findings and time to mortality, adjusting for sex and clinical risk factors. Major adverse cardiovascular events (MACE) were assessed in a subgroup (n=4,413). Results: At a mean 5.6±1.1yr follow-up, CTCA-identified CAD predicted increased mortality compared to patients with a normal CTCA in both <70yrs [non-obstructive HR (CI): 1.70 (1.19–2.41); one-vessel: 1.65 (1.30–2.67); two-vessel: 2.24 (1.21–4.15); three-vessel/left main: 4.12 (2.27–7.46), p<0.001] and ≥70yrs [non-obstructive: 1.84 (1.15–2.95); one-vessel: HR (CI): 2.28 (1.37–3.81); two-vessel: 2.36 (1.33–4.19); three-vessel/left main: 2.41 (1.33–4.36), p=0.014]. CTCA findings similarly predicted long-term MACE in both groups. In a subgroup of very elderly patients ≥75yrs, CTCA remained predictive of MACE (n=417) [non-obstructive HR 1.60 (0.90–2.83); one-vessel: 2.15 (1.13–4.08); two-vessel: 3.51 (1.75–7.01); three-vessel/left main: 2.42 (1.19–4.92), p=0.001], but not mortality (n=956) [non-obstructive 1.39 (0.81–2.36); one-vessel: 1.54 (0.86–2.76); two-vessel: 1.60 (0.84–3.04); three-vessel/left main: 1.67 (0.87–3.20), p=0.55] after adjustment for clinical risk factors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".