Prediction of Familial Hypercholesterolemia in Patients at High Atherosclerotic Cardiovascular Disease Risk Using a Recently Validated Algorithm
Bibliographic record
Abstract
BACKGROUND: argets (REACT) registry. METHODS: Patients were enrolled as ASCVD (n = 86) or FH (n = 109) and with an LDL-C level > 3.0 mmol/L despite maximally tolerated statin therapy. FH was diagnosed clinically using a validated clinical application integrating an imputation for baseline (untreated) LDL-C levels. RESULTS: There were 109 men and 86 women with a mean age of 63 ± 12 years. Diabetes (29.7%), hypertension (62.1%), smoking (37.9%), and family history of premature ASCVD (59.5%) were common. On-treatment LDL-C was 4.26 ± 0.94 mmol/L. On the basis of the dose and type of statin ± ezetimibe, imputed baseline LDL-C was 7.04 ± 2.90 mmol/L. A diagnosis of probable/definite FH was found in 54.7%, 49.5%, and 61.5% of patients according to the Simon Broome, Dutch Lipid Clinic Network criteria, and the new Canadian FH definition, respectively. Of note, 40% of patients in the ASCVD inclusion subgroup had probable or definite FH. CONCLUSIONS: Our study reveals that a substantial proportion of patients with ASCVD whose LDL-C levels are > 3.0 mmol/L despite maximally tolerated statins have heterozygous FH. Clinicians should consider using the recently described algorithm to assess the possibility of FH in this high-risk population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".