Correlation of TG/HDL Ratio and LDL/HDL Ratio with The Incidence of Coronary Artery Disease (CAD) at General Hospital of Buleleng Regency
Bibliographic record
Abstract
Background: CAD is a leading cause of death in both industrialised and developing nations, primarily affecting the younger generation. Triglycerides (TG) to high-density lipoprotein (HDL) cholesterol ratios (TG/HDL) and low-density lipoprotein (LDL) to HDL ratios (LDL/HDL) have been linked to cardiovascular disease. Objective: The objective of this research is to ascertain the relationship between the incidence of CAD and the TG/HDL and LDL/HDL ratios. Method: Analytical observational study with a cross-sectional approach conducted on 210 CAD patients at General Hospital of Buleleng Regency in 2024-2025. Data analysis was performed using the SPSS. Determination of the cut-off value was carried out using the Receiver Operating Characteristic (ROC) curve, then followed by chi-square analysis and logistic regression. Results: Average age of the sample was 60.53 ± 12.647 years and the majority were <65 years old (67.6%). Based on the ROC curve, the cut-off value for the TG/HDL ratio was 2.84 (AUC= 0.45; 95%CI (0.302-0.508); p<0.07) and LDL/HDL ratio was 2.38 (AUC= 0.503; 95%CI (0.398-0.608); p<0.96). Based on the chi-square test, there was no significant relationship between the TG/HDL ratio (OR=1.71; 95%CI=0.92-3.17; p=0.08) or the LDL/HDL ratio (OR=0.94; 95%CI=0.52-1.70; p=0.85) with the incidence of CAD. Based on multivariate analysis, a significant relationship was obtained between a high TG/HDL ratio and the incidence of CAD (AOR=0.42; 95%CI=1.88-0.979; p=0.04). Conclusion: There is a significant relationship between a high TG/HDL ratio and the incidence of CAD.
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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 | 0.012 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".