Increased FH-Risk-Score and Diabetes Are Cardiovascular Risk Equivalents in Heterozygous Familial Hypercholesterolemia
Bibliographic record
Abstract
BACKGROUND: Familial hypercholesterolemia (FH) is a genetic condition causing premature atherosclerotic cardiovascular disease (ASCVD). It is well established that patients with FH should be treated with statin therapy. However, there exists discordance concerning low-density lipoprotein cholesterol-lowering goals in the management of these patients between different guidelines worldwide. The objective was to compare the 10-year ASCVD risk of different subgroups of patients with and without FH including those with diabetes or a history of ASCVD and patients with FH within different FH-Risk-Score categories. METHODS: This multinational observational study used data from 3 different prospective cohorts. A total of 3383 FH and 6917 non-FH controls matched for age and sex were included (104 363 person-years of follow-up). The 10-year incident ASCVD risk was assessed using Kaplan-Meier estimates, whereas the relative risk was estimated using Cox proportional hazards regression models. RESULTS: <0.0001). CONCLUSIONS: This study strongly suggests that the observed risk of FH patients with diabetes, history of ASCVD, and FH-Risk-Score >20% is as high or higher than non-FH individuals with a history of ASCVD. More aggressive management should be recommended for these patients.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".