Prognostic value of chronic total occlusions detected on coronary computed tomographic angiography
Bibliographic record
Abstract
OBJECTIVE: Data describing clinical relevance of chronic total occlusion (CTO) identified by coronary CT angiography (CCTA) have not been reported to date. We investigated the prognosis of CTO on CCTA. METHODS: We identified 22 828 patients without prior known coronary artery disease (CAD), who were followed for a median of 26 months. Based on CCTA, coronary lesions were graded as normal (no atherosclerosis), non-obstructive (1%-49%), moderate-to-severe (50%-99%) or totally occluded (100%). All-cause mortality, and major adverse cardiac events defined as mortality, non-fatal myocardial infarction and late coronary revascularisation (≥90 days after CCTA) were assessed. RESULTS: The distribution of patients with normal coronaries, non-obstructive CAD, moderate-to-severe CAD and CTO was 10 034 (44%), 7965 (34.9%), 4598 (20.1%) and 231 (1%), respectively. The mortality rate per 1000 person-years of CTO patients was non-significantly different from patients with moderate-to-severe CAD (22.95; 95% CI 12.71 to 41.45 vs 14.46; 95% CI 12.34 to 16.94; p=0.163), and significantly higher than of those with normal coronaries and non-obstructive CAD (p<0.001 for both). Among 14 382 individuals with follow-up for the composite end point, patients with CTO had a higher rate of events than those with moderate-to-severe CAD (106.56; 95% CI 76.51 to 148.42 vs 65.45; 95% CI 58.01 to 73.84, p=0.009). This difference was primarily driven by an increase in late revascularisations in CTO patients (27 of 35 events). After multivariable adjustment, compared with individuals with normal coronaries, the presence of CTO conferred the highest risk for adverse cardiac events (14.54; 95% CI 9.11 to 23.20, p<0.001). CONCLUSIONS: The detection of CTO on non-invasive CCTA is associated with increased rate of late revascularisation but similar 2-year mortality as compared with moderate-to-severe CAD. TRIAL REGISTRATION NUMBER: NCT01443637.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| 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".