Left Ventricular Function and Volume with Coronary CT Angiography Improves Risk Stratification and Identification of Patients at Risk for Incident Mortality: Results from 7758 Patients in the Prospective Multinational CONFIRM Observational Cohort Study
Bibliographic record
Abstract
PURPOSE: To assess whether gradations of left ventricular (LV) ejection fraction (LVEF) and volumes measured with coronary computed tomography (CT) would augment risk stratification and discrimination for incident mortality. MATERIALS AND METHODS: This study was approved by the institutional review board, and informed consent was obtained when required. Subjects without known coronary artery disease (CAD) who underwent cardiac CT angiography with quantitative LV measurements were categorized according to LVEF (≥ 55%, 45%-54.9%, 35%-44.9%, or <35%). LV end-systolic volume (LVESV) and LV end-diastolic volume (LVEDV) were classified as normal (≥ 90 mL) or abnormal (≥ 200 mL). CAD extent and severity was categorized as none, nonobstructive, obstructive (≥ 50%), one-vessel, two-vessel, and three-vessel or left main disease. LVEF and volumes were assessed for risk prediction and discrimination of future mortality by using Cox hazards model and receiver operating characteristic curve analysis, respectively. RESULTS: During a follow-up of 2.0 years ± 0.9, 7758 patients (mean age, 58.5 years ± 13.0; 4220 male patients [54.4%]) were studied. At multivariable analysis, worsening LVEF was independently associated with mortality for moderately (hazard ratio = 3.14, P < .001) and severely (hazard ratio = 5.19, P < .001) abnormal ejection fraction. LVEF demonstrated improved discrimination for mortality (Az = 0.816) when compared with CAD risk factors alone (Az = 0.781) or CAD risk factors plus extent and severity. At multivariable analysis of a subgroup of 3706 individuals, abnormal LVEDV (hazard ratio = 4.02) and LVESV (hazard ratio = 6.46) helped predict mortality (P < .001). Similarly, LVESV and LVEDV demonstrated improved discrimination when compared with CAD risk factors or CAD extent and severity (P < .05). CONCLUSION: LV dysfunction and volumes measured with cardiac CT angiography augment risk prediction and discrimination for future mortality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".