Identification and Treatment of Patients with Homozygous Familial Hypercholesterolaemia: Information and Recommendations from a Middle East Advisory Panel
Bibliographic record
Abstract
We present clinical practice guidelines for the diagnosis and treatment of homozygous familial hypercholesterolaemia (HoFH) in the Middle East region. While guidelines are broadly applicable in Europe, in the Middle East we experience a range of confounding factors that complicate disease management to a point whereby the European guidance cannot be applied without significant modification. Specifically, for disease prevalence, the Middle East region has an established epidemic of diabetes and metabolic syndrome that can complicate treatment and mask a clinical diagnosis of HoFH. We have also a high incidence of consanguineous marriages, which increase the risk of transmission of recessive and homozygous genetic disorders. This risk is further augmented in autosomal dominant disorders such as familial hypercholesterolaemia (FH), in which a range of defective genes can be transmitted, all of which contribute to the phenotypic expression of the disease. In terms of treatment, we do not have access to lipoprotein apheresis on the same scale as in Europe, and there remains a significant reliance on statins, ezetimibe and the older plasma exchange methods. Additionally, we do not have widespread access to anti-apolipoprotein B therapies and microsomal transfer protein inhibitors. In order to adapt existing global guidance documents on HoFH to the Middle East region, we convened a panel of experts from Oman, Saudi Arabia, UAE, Iran and Bahrain to draft a regional guidance document for HoFH. We also included selected experts from outside the region. This panel statement will form the foundation of a detailed appraisal of the current FH management in the Middle Eastern population and thereby provide a suitable set of guidelines tailored for the region.
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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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".