Small Dense Low-Density Lipoprotein for Risk Prediction of Acute Coronary Syndrome
Bibliographic record
Abstract
BACKGROUND: Elevated Low density Lipoprotein (LDL) levels have been traditionally associated with development of atherosclerotic coronary artery disease (CAD). As LDL-cholesterol levels are not always raised in acute coronary syndrome (ACS) patients, sd-LDL is an emerging risk factor. The purpose of the present study was tri-fold. Firstly, it aimed to investigate the association of sd-LDL as a risk factor in ACS patients. Secondly, it aimed to correlate the presence of sd-LDL with severity of coronary artery disease as determined by coronary angiography. Lastly, it aimed to correlate the presence of sd-LDL with short-term outcomes. METHODS: This was a prospective, hospital-based, cross-sectional, case-control study conducted over a 1-year study duration. Patients above the age of 18 years diagnosed with ACS within 24 h of admission were studied. Blood samples were collected after all patients had undergone coronary angiography and sd-LDL levels were measured. RESULTS: ACS patients had significantly higher sd-LDL levels than non-ACS patients (16.10 ± 1.42 mg/dL vs. 12.67 ± 0.71 mg/dL, P = 0.036). Males had significantly higher sd-LDL levels than females (16.79 ± 1.55 mg/dl vs. 10.77 ± 2.62 mg/dl, P=0.047). Patients with non-left anterior descending coronary artery (LAD) involvement had significantly higher sd-LDL levels compared to patients with LAD involvement (21.92 ± 3.55 mg/dL vs. 14.03 ± 1.35 mg/dL, P = 0.007). CONCLUSION: These results suggest that sd-LDL is a risk factor for the development of ACS in an Indian population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".