Association Between the Level of Low-Density Lipoprotein Cholesterol and Coronary Atherosclerosis in Patients Who Have Undergone Coronary Computed Tomography Angiography
Bibliographic record
Abstract
BACKGROUND: Although the Japan Atherosclerosis Society Guidelines 2017 recommend lower levels of low-density lipoprotein cholesterol (LDL-C, < 70 mg/dL or ≤ 100 mg/dL) to prevent secondary cardiovascular events, we cannot conclude that a low level of LDL-C prevents primary cardiovascular events in patients with suspected coronary artery disease (CAD). METHODS: We registered 1,016 patients who were clinically suspected to have CAD and who underwent coronary computed tomography angiography (CCTA) for screening of coronary atherosclerosis. We excluded 350 patients who were receiving anti-lipidemic therapies and finally analyzed 666 patients. The patients were divided into three groups according to the LDL-C level: < 70 mg/dL (n = 25, Low LDL-C), 70 - 99 mg/dL (n = 141, Middle LDL-C), and ≥ 100 mg/dL (n = 500, High LDL-C). A ≥ 50% coronary stenosis was initially diagnosed as CAD, and the number of significantly stenosed coronary vessels (VD), Gensini score and coronary artery calcification (CAC) score were quantified. RESULTS: There were no significant differences in age, high-density lipoprotein cholesterol, rates of hypertension, hemoglobin A1c, blood sugar or systolic blood pressure among the Low, Middle and High LDL-C groups. On the other hand, there were significant differences in rates of males, smoking, dyslipidemia and diabetes, diastolic blood pressure and triglyceride among the groups. The prevalence of CAD values in the Low, Middle and High LDL-C groups were similar, at 52%, 47%, and 46%, respectively. In addition, there were no significant differences in the number of VD, Gensini score or CAC score among the Low LDL-C, Middle LDL-C and High LDL-C groups. CONCLUSIONS: We showed that the level of LDL-C was not associated with the presence or severity of CAD, which indicates that we need to screen by CCTA to prevent primary coronary events even if patients without anti-lipidemic therapies show low levels of LDL-C.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".