Real-world risk of cardiovascular outcomes associated with hypertriglyceridaemia among individuals with atherosclerotic cardiovascular disease and potential eligibility for emerging therapies
Bibliographic record
Abstract
AIMS: Hypertriglyceridaemia in patients with atherosclerotic cardiovascular disease (ASCVD) has been in focus following the REDUCE-IT trial showing benefit with icosapent ethyl. Among individuals with prevalent ASCVD, we sought to quantify the contemporary, real-world risk of ASCVD events associated with hypertriglyceridaemia, as well as estimate icosapent ethyl eligibility and compare trial participants with REDUCE-IT-like individuals in the population. METHODS AND RESULTS: We examined data from 2 424 865 adults with lipid panels in the Ontario population. Among those with prevalent ASCVD, we examined adjusted associations between triglyceride (TG) and ASCVD events (first occurrence of myocardial infarction, unstable angina, stroke or transient ischaemic attack, coronary revascularization, or cardiovascular death). The proportion of patients with ASCVD potentially eligible for icosapent ethyl was estimated as those with TG 135-499 mg/dL (1.52-5.63 mmol/L) and low-density lipoprotein cholesterol (LDLc) 41-100 mg/dL (1.06-2.59 mmol/L), similar to the lipid cut-offs in REDUCE-IT, and their demographics and event rates examined. Among 196 717 individuals with ASCVD, median age was 69 years and 30% were female. A total of 24 097 composite ASCVD events occurred over a mean (standard deviation) 2.9 (0.5) years of follow-up. Increasing TG was associated with a graded, progressively higher hazard of ASCVD events. Twenty-five percent (49 886) of individuals with ASCVD had hypertriglyceridaemia and controlled LDLc; these patients were demographically similar to those in REDUCE-IT with comparable event rates. CONCLUSIONS: Among patients with ASCVD, hypertriglyceridaemia is common, and is associated with higher ASCVD risk across a range of TG. It is possible that as many as one in four patients with ASCVD may be candidates for emerging therapies.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| 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".