Real-World Risk of Recurrent Cardiovascular Events in Atherosclerotic Cardiovascular Disease Patients with LDL-C Above Guideline-Recommended Threshold: A Retrospective Observational Study
Bibliographic record
Abstract
INTRODUCTION: The 2021 Canadian Cardiovascular Society (CCS) guidelines recommend intensive low-density lipoprotein cholesterol (LDL-C) reduction for patients with atherosclerotic cardiovascular disease (ASCVD). For patients above LDL-C threshold on maximally tolerated statins, adding ezetimibe and/or a proprotein convertase subtilisin/kexin type 9 inhibitor (PCSK9i) is recommended. This population-based, real-world study examined cardiovascular (CV) events in patients with ASCVD who are on statins and above current guideline threshold LDL-C levels. METHODS: Using administrative health data in Alberta, Canada, we identified patients with myocardial infarction (MI), ischemic stroke (IS), or peripheral artery disease with LDL-C > 1.8 mmol/L on statins between April 1, 2010 and March 31, 2016. Exploratory subgroups included very high-risk patients with ASCVD shown to derive the most benefit from PCSK9i intensification as identified by the CCS guidelines, including those with acute coronary syndrome (ACS) or recent MI. Frequencies and rates of individual and composite CV events (primary outcome: MI, IS, hospitalization for unstable angina, coronary revascularization, cardiovascular death; secondary outcome: MI, IS, CV death) were calculated over follow-up. RESULTS: The study included 32,984 patients with a mean (standard deviation) follow-up of 40.8 (21.0) months. Overall, 17.7% and 15.6% experienced a primary and secondary outcome, respectively, with rates of 5.58 and 4.83 per 100 patient-years, respectively. CV death and MI were the most common events. Subgroups with recurrent MI and comorbid diabetes exhibited higher CV event rates (23.6% and 22.2% had a primary outcome, respectively). Rates of CV events were notably high in patients with ACS or recent MI (49.4% and 54.0% had a primary outcome, respectively). CONCLUSION: This real-world study confirms that statin-treated high-risk patients with ASCVD and above-threshold LDL-C levels have substantial incidence of recurrent CV events. These findings reinforce the opportunity for lipid-lowering therapy intensification in high-risk patients to levels below guideline-recommended threshold in order to reduce CV risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".