Relationship between ischaemia, coronary artery calcium scores, and major adverse cardiovascular events
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Positron emission tomography (PET) myocardial perfusion imaging (MPI) is often combined with coronary artery calcium (CAC) scanning, allowing for a combined anatomic and functional assessment. We evaluated the independent prognostic value of quantitative assessment of myocardial perfusion and CAC scores in patients undergoing PET. METHODS AND RESULTS: Consecutive patients who underwent Rb-82 PET with CAC scoring between 2010 and 2018, with follow-up for major adverse cardiovascular events (MACE), were identified. Perfusion was quantified automatically with total perfusion deficit (TPD). Our primary outcome was MACE including all-cause mortality, myocardial infarction (MI), admission for unstable angina, and late revascularization. Associations with MACE were assessed using multivariable Cox models adjusted for age, sex, medical history, and MPI findings including myocardial flow reserve.In total, 2507 patients were included with median age 70. During median follow-up of 3.9 years (interquartile range 2.1-6.1), 594 patients experienced at least one MACE. Increasing CAC and ischaemic TPD were associated with increased MACE, with the highest risk associated with CAC > 1000 [adjusted hazard ratio (HR) 1.67, 95% CI 1.24-2.26] and ischaemic TPD > 10% (adjusted HR 1.80, 95% CI 1.40-2.32). Ischaemic TPD and CAC improved overall patient classification, but ischaemic TPD improved classification of patients who experienced MACE while CAC mostly improved classification of low-risk patients. CONCLUSIONS: Ischaemic TPD and CAC were independently associated with MACE. Combining extent of atherosclerosis and functional measures improves the prediction of MACE risk, with CAC 0 identifying low-risk patients and regional ischaemia identifying high-risk patients in those with CAC > 0.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it