Association Between Major Adverse Cardiovascular Events and Left Ventricular Mass Index in Patients Who Have Undergone Coronary Computed Tomography Angiography: From the FU-CCTA Registry
Bibliographic record
Abstract
Background: Left ventricular mass (LVM) is a predictor of future cardiovascular risk. We determined the association between LVM measured by coronary computed tomography angiography (CCTA) and the prognosis in patients who have undergone CCTA for screening of coronary artery disease (CAD). Methods: We performed a prospective cohort study. Five hundred twenty consecutive patients who underwent CCTA at Fukuoka University Hospital (FU-CCTA registry) were enrolled. They were clinically suspected of having CAD or had at least one cardiovascular risk factor, and were a follow-up of up to 5 years. Equal to more than 50% of coronary stenosis as assessed by CCTA was diagnosed as CAD. Using CCTA, LVM index (LVMI), LV ejection fraction (LVEF), LV end-diastolic volume (LVEDV) and LV end-systolic volume were measured. The primary endpoint was major adverse cardiovascular events (MACEs: including all causes of death, ischemic stroke, acute myocardial infarction and coronary revascularization). The patients were divided into non-MACEs and MACEs groups. Results: The non-MACEs and MACEs groups consisted of 478 and 42 patients, respectively. Percent of CAD in the MACEs group was significantly higher than that in the non-MACEs group. The MACEs group showed significantly higher LVMI and tended to have a lower LVEF and LVEDV than the non-MACEs group. Although LVMI was not associated with MACEs in all patients, LVMI was independently associated with MACEs in males (odd ratio: 1.018, 95% confidence interval: 1.002 - 1.035, P = 0.030), but not females. Conclusions: Evaluation of LVMI by CCTA may be useful for predicting MACEs in males.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".