2023 Update on European Atherosclerosis Society Consensus Statement on Homozygous Familial Hypercholesterolaemia: new treatments and clinical guidance
Bibliographic record
Abstract
This 2023 statement updates clinical guidance for homozygous familial hypercholesterolaemia (HoFH), explains the genetic complexity, and provides pragmatic recommendations to address inequities in HoFH care worldwide. Key strengths include updated criteria for the clinical diagnosis of HoFH and the recommendation to prioritize phenotypic features over genotype. Thus, a low-density lipoprotein cholesterol (LDL-C) >10 mmol/L (>400 mg/dL) is suggestive of HoFH and warrants further evaluation. The statement also provides state-of-the art discussion and guidance to clinicians for interpreting the results of genetic testing and for family planning and pregnancy. Therapeutic decisions are based on the LDL-C level. Combination LDL-C-lowering therapy-both pharmacologic intervention and lipoprotein apheresis (LA)-is foundational. Addition of novel, efficacious therapies (i.e. inhibitors of proprotein convertase subtilisin/kexin type 9, followed by evinacumab and/or lomitapide) offers potential to attain LDL-C goal or reduce the need for LA. To improve HoFH care around the world, the statement recommends the creation of national screening programmes, education to improve awareness, and management guidelines that account for the local realities of care, including access to specialist centres, treatments, and cost. This updated statement provides guidance that is crucial to early diagnosis, better care, and improved cardiovascular health for patients with HoFH worldwide.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.022 |
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".