Patient Perspectives Regarding Genetic Testing for Familial Hypercholesterolemia
Bibliographic record
Abstract
Background Familial hypercholesterolemia (FH) is a common genetic disorder resulting in high levels of low-density lipoprotein cholesterol and increased risk of atherosclerotic cardiovascular disease. Genetic testing for FH is recommended but is not available in most of Canada. Consequently, there is a paucity of data regarding patient experiences with genetic testing. The objectives of this study were to investigate the attitudes and perspectives of patients with FH who underwent genetic testing. Methods We administered an anonymous online survey to participants in the British Columbia Familial Hypercholesterolemia Registry who had undergone research-based genetic testing for FH. The survey included 25 questions and explored patients' experiences with the genetic testing process, willingness to recommend genetic screening, and motivation to lower cholesterol levels. Results Among 183 respondents, 38 (20.7%) had a positive genetic test result, 27 (14.8%) had a negative result, and 118 (64.4%) were awaiting their results. Compared with individuals awaiting their test results, participants with a positive genetic test were more likely to believe lipid-lowering therapy was highly important (74.3% vs 55.4%; P = 0.05). They were also more likely to strongly agree that a diagnosis of FH was important to them (71.1% vs 46.2%; P = 0.008), and were more likely to recommend genetic screening to their family members (85.9% vs 72.9%; P = 0.04). Conclusions To our knowledge, this is the first study in Canada to explore the perspectives of patients with FH who underwent genetic testing. These results suggest that genetic testing for FH might offer benefits in important patient-centred outcomes.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".