Lipid-Lowering Therapy in Post-Acute Coronary Syndrome Patients: An Observational Study
Bibliographic record
Abstract
Background: Cardiovascular disease remains a major cause of morbidity and mortality globally. International guidelines recommend aggressive lipid-lowering therapy (LLT) in patients with atherosclerotic cardiovascular disease (ASCVD), targeting a low-density lipoprotein cholesterol (LDL-C) level of < 55 mg/dL and a ≥ 50% reduction from baseline. However, real-world studies continue to show suboptimal LDL-C target achievement. This study aimed to assess the proportion of post-acute coronary syndrome (ACS) patients achieving both LDL-C < 55 mg/dL and a ≥ 50% reduction from baseline at 6 months. A secondary objective was to evaluate target achievement after 1 year and analyze outcomes across different LLT regimens. Methods: We conducted a retrospective cohort study at a single tertiary center, including patients aged ≥ 18 years who presented with ACS between January 2021 and January 2022, underwent percutaneous coronary intervention (PCI), and had documented LDL-C levels at baseline and at least one follow-up within 12 months. Patients with baseline LDL-C ≤ 55 mg/dL or on ongoing LLT were excluded. Results: A total of 122 patients were included (mean age 63.5 years; 59.8% had both diabetes and hypertension). At 6 months, only 13/82 patients (15.9%) achieved the primary LDL-C target. The highest achievement was seen in the rosuvastatin + ezetimibe group (30.0%), followed by rosuvastatin (17.9%), atorvastatin + ezetimibe (14.3%), and atorvastatin monotherapy (14.0%). A ≥ 50% LDL-C reduction without meeting the < 55 mg/dL threshold was observed in 24/82 patients (29.3%). Conclusions: LDL-C target achievement remains low among post-ACS patients despite high-intensity statin use. Combination therapy with rosuvastatin + ezetimibe showed more favorable outcomes, particularly in older adults. These findings underscore the need for structured follow-up, treatment intensification, and broader use of advanced therapies such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors to close the real-world treatment gap.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".