Evaluation of Lipid Profile in Patients with Cardiovascular Diseases Receiving Simvastatin in Palu Indonesia
Bibliographic record
Abstract
Cardiovascular diseases (CVDs) are the leading cause of death worldwide which results from the impaired function of the heart and blood vessels. The most common CVDs are coronary heart and stroke. The main clinical manifestation of these diseases is the formation of atherosclerosis which is associated with the change of blood lipid levels. Simvastatin is widely used in patients with impaired lipid levels in the blood. The study was a descriptive research with a retrospective approach on medical record data (n=64) taken from Palu City, Central Sulawesi, Indonesia. The variables included in this study were gender, age, diagnosis, co-medication, lipid profile including total cholesterol, LDL, triglycerides, and HDL in patients with CVDs receiving simvastatin. In the study, sixty-four patients of CVDs met the inclusion and exclusion criteria. This study suggested that simvastatin achieved to normalize the blood lipid levels, including total cholesterol in forty-four patients (68.75%), LDL in forty-nine patients (80.3%), triglycerides in fifty-nine patients (92.19%), and HDL in fifty-two patients (81.25%). The use of simvastatin in patients with CVDs managed to lower total cholesterol, LDL, and triglycerides, as well as increase the HDL level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".