Normalized Subendocardial Myocardial Attenuation on Coronary Computed Tomography Angiography Predicts Postoperative Adverse Cardiovascular Events: Coronary CTA VISION Substudy
Bibliographic record
Abstract
Background: Abnormalities in computed tomography myocardial perfusion has been associated with coronary artery disease and major adverse cardiovascular events (MACE). We sought to investigate if subendocardial attenuation using coronary computed tomography angiography predicts MACE 30 days postelective noncardiac surgery. Methods: Using a 17-segment model, coronary computed tomography angiography images were analyzed for subendocardial and transmural attenuation and the corresponding blood pool. The segment with the lowest subendocardial attenuation and transmural attenuation were normalized to the segment with the highest subendocardial and transmural attenuation, respectively (SUB normalized , and TRANS normalized , respectively). We evaluated the independent and incremental value of myocardial attenuation to predict the composite of cardiovascular death or nonfatal myocardial infarction. Results: Of a total of 995 coronary CTA VISION (Coronary Computed Tomographic Angiography and Vascular Events in Noncardiac Surgery Patients Cohort Evaluation Study) patients, 735 had available images and complete data for these analyses. Among these patients, 60 had MACE. Based on Revised Cardiovascular Risk Index, 257, 302, 138, and 38 patients had scores of 0, 1, 2, and ≥3, respectively. On coronary computed tomography angiography, 75 patients had normal coronary arteries, 297 patients had nonobstructive coronary artery disease, 264 patients had obstructive disease, and 99 patients had extensive obstructive coronary artery disease. SUB normalized was an independent and incremental predictor of events in the model that included Revised Cardiovascular Risk Index and coronary artery disease severity. Compared with patients in the highest tertile of SUB normalized , patients in the second and first tertiles had an increased hazards ratio for events (2.23 [95% CI, 1.091–4.551] and 2.36 [95% CI, 1.16–4.81], respectively). TRANS normalized , as a continuous variable, was also found to be a predictor of MACE ( P =0.027). Conclusions: Our study demonstrates that SUB normalized and TRANS normalized are independent and incremental predictors of MACE 30 days after elective noncardiac surgery. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01635309.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".