Contemporary Trends in the Management and Outcomes of Patients With Familial Hypercholesterolemia in Canada: A Prospective Observational Study
Bibliographic record
Abstract
BACKGROUND: Heterozygous familial hypercholesterolemia (HeFH) is one of the most common genetic diseases in the world and an important cause of premature cardiovascular (CV) disease. The purpose of this study was to characterize the clinical features, current treatment patterns, and CV outcomes of patients with HeFH in British Columbia, Canada. METHODS: We conducted a longitudinal observational study of patients with HeFH attending a specialized lipid clinic. We collected data on lipid levels, medication use, and CV events at baseline and last follow-up. RESULTS: We recruited 339 patients with clinically diagnosed HeFH, with a total of 3700 person-years of follow-up. The mean low-density lipoprotein cholesterol (LDL-C) level was 5.9 mmol/L at baseline and 3.7 mmol/L at last follow-up. Use of lipid-lowering therapy (LLT) increased from 35.7% at baseline to 84.7% at last follow-up. A ≥ 50% reduction in LDL-C level was achieved in 34.5% of patients, and an LDL-C level ≤ 2 mmol/L was seen in 8.3%. The overall CV event rate in this cohort was 33.5/1000 person-years. Among patients who had a CV event during follow-up, 59% experienced a recurrent event within 5 years. CONCLUSIONS: These data contribute to our understanding of contemporary trends in the management of patients with HeFH in Canada. Despite a majority of patients receiving LLT, few patients reached high-risk lipid targets. These data highlight important opportunities to improve the care of patients with HeFH.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".