Association of lipid target achievement and cardiovascular outcomes following statin initiation: a population-based cohort study
Bibliographic record
Abstract
Abstract Introduction Non-high density lipoprotein cholesterol (non-HDL-C) is increasingly incorporated into clinical practice guidelines along with low density lipoprotein cholesterol (LDL-C) to guide lipid-lowering therapy decisions. We aimed to examine patterns of LDL-C and non-HDL-C levels after statin initiation for primary prevention of cardiovascular disease (CVD), and their association with incident CV events. Methods We conducted a population-based cohort study of Ontario, Canada residents age ≥66 years who initiated a statin for primary prevention between January 1, 2012 and December 31, 2019. For those surviving 1-year after statin initiation, we determined the proportion with a lipid panel in the 1-year period after a statin was started. For those with a lipid panel, we used the lipid panel closest to the end of the 1-year period to categorize individuals based on the LDL-C and non-HDL-C thresholds in the 2021 Canadian Cardiovascular Society dyslipidemia guidelines (Table 1). We stratified by diabetes/chronic kidney disease (CKD) status. We evaluated the association between LDL-C/non-HDL-C category and a composite of all-cause mortality or hospitalization for myocardial infarction, stroke or revascularization (primary outcome). We also investigated the association between each category and each component of the primary outcome. The index date was the 365 days after a statin was initiated and follow-up was until December 31, 2020. We used a cause-specific hazards model for analysis, adjusted for clinical and sociodemographic confounders. Results Our cohort comprised 173,127 people. In the 1-year period after statin initiation, 72% of people had a follow-up lipid panel performed. Median follow-up after that was 2.5 years. Compared with those meeting both LDL-C and non-HDL-C targets, being above both targets was associated with an increased rate of the primary outcome for people without diabetes/CKD (HR 1.10, 95% CI 1.05 to 1.15) and those with diabetes/CKD (HR 1.16, 95% CI 1.09 to 1.23). Being at LDL-C target but above non-HDL-C target was associated with an increased rate of the primary outcome for people with diabetes/CKD (HR 1.16, 95% CI 1.03 to 1.30) but not for those without diabetes/CKD (HR 1.05, 95% CI 0.93 to 1.17). Conclusions In this population-based cohort, having an LDL-C and non-HDL-C above guideline-recommended targets after statin initiation was associated with an increased rate of adverse outcomes. These findings support the residual risk associated with incompletely controlled LDL-C or non-HDL-C levels after initiating statin therapy for primary prevention.Primary outcome associationsComponents of primary outcome
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".