Preliminary Observations on Discordance Between Coronary Artery Calcium Score of Zero and Coronary Computed Tomography Angiography Findings in Asymptomatic Adults
Bibliographic record
Abstract
Background: Coronary artery calcium (CAC) scoring is widely used to screen for coronary artery disease (CAD) in asymptomatic individuals. However, it detects calcified plaques and may miss non-calcified or soft plaques. This study compared the diagnostic accuracy of CAC scoring with coronary computed tomography angiography (CCTA) for detecting CAD in asymptomatic individuals with risk factors. Methods: Eighteen asymptomatic adults with a CAC score of 0 underwent CCTA to evaluate for subclinical CAD. Clinical, biochemical, and lifestyle risk factors were assessed. Diagnostic agreement between CAC and CCTA was analyzed using the Wilcoxon signed rank test. Results: . Smoking (70.5%) and family history of CAD (56.25%) were prevalent. Biochemical analyses showed preserved renal function and non-diabetic glycemic profiles. Despite the absence of calcification on CAC, CCTA revealed CAD in 72.2% (13/18) of participants, detecting non-calcified plaques missed by CAC scoring. Elevated cardiac and inflammatory markers, including high-sensitivity cardiac troponin T, apolipoprotein B (apoB), and lipoprotein(a) (Lp(a)), were observed in those with positive CCTA findings. The Wilcoxon signed rank test indicated a significant difference between the modalities (Z = -3.606, P < 0.001). Conclusions: CCTA detected non-calcified atherosclerosis missed by CAC and demonstrated superior sensitivity for early CAD detection in asymptomatic individuals.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".