Cost Effectiveness of Coronary Calcification Scanning Using Electron Beam Tomography in Intermediate and High Risk Asymptomatic Individuals
Bibliographic record
Abstract
Pharmaceutical therapy of hyperlipidemia is clearly beneficial. In the patient without established heart disease however, conventional risk assessment is imprecise and determining which patients are at highest versus lowest risk is a common clinical conundrum. It is well established that the most powerful determinant to risk is the overall extent/severity of coronary disease. Electron beam tomography (EBT) and quantification of coronary artery calcium has been shown to provide a valid non-invasive surrogate to atherosclerotic plaque burden. Screening patients who are considered to be at traditional intermediate to high risk by first using EBT can refine the broad-based population risk to a more individual basis. Data that is based upon a model developed for application of EBT are presented, which discuss its potential as a cost effective application to guide statin therapy in intermediate and high-risk sub-groups.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".