Is Deprescription of Ezetimibe Safe in Familial Hypercholesterolemia Patients Taking Evolocumab?
Bibliographic record
Abstract
We evaluated whether low-density lipoprotein cholesterol (LDL-C) levels in familial hypercholesterolemia patients on triple lipid-lowering therapy would remain below intensification threshold values after withdrawal of ezetimibe. We included 13 heterozygous familial hypercholesterolemia patients with vascular disease who were treated with statin + ezetimibe + evolocumab; ezetimibe was discontinued at the patients' request. After 3 months, LDL-C levels increased from 0.96 ± 0.51 to 1.54 ± 1.07 mmol/L. In 12 of 13 patients, the LDL-C level remained below 1.8 mmol/L. No adverse cardiovascular events were observed. Deprescribing ezetimibe reduced pill burden but increased LDL-C level, although usually not above the treatment intensification threshold for high-risk patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".