Colesevelam hydrochloride in the management of dyslipidemia
Bibliographic record
Abstract
Dyslipidemia is a highly heterogeneous group of disorders strongly influenced by both genetic and environmental factors. Dyslipidemia significantly increases risk for atherosclerotic disease and all of its various clinical manifestations. Identifying patients with dyslipidemia and initiating therapies aimed at normalizing the lipid profile has been demonstrated to significantly reduce the risk for myocardial infarction, stroke and cardiovascular mortality in both the primary and secondary prevention settings. Guidelines in Europe, Canada and the USA emphasize the need to reduce the burden of atherogenic lipoproteins in serum and to raise levels of high-density lipoproteins in patients at risk for cardiovascular events. Statins have emerged as front-line therapy for managing dyslipidemia, especially in patients with elevated serum levels of low-density lipoprotein cholesterol. As guidelines emphasize the need to reduce serum low-density lipoprotein cholesterol to lower levels, goal attainment can be challenging. The use of combination therapy increases the likelihood of therapeutic success for many patients. Furthermore, a significant percentage of patients with dyslipidemia either cannot achieve goals on statin monotherapy, choose not to take a statin or do not tolerate these drugs due to adverse side effects, such as myalgias, weakness or hepatotoxicity. This article summarizes the pharmacology, clinical efficacy and safety of colesevelam hydrochloride, a bile acid-binding resin. Bile acid-binding resins are orally administered anion-exchange resins that are not absorbed systemically. These agents bind bile acids and reduce their reabsorption at the level of the terminal ileum and prevent their enterohepatic recirculation. Colesevelam has a favorable side effect and toxicity profile and significantly impacts serum levels of lipoproteins when used as monotherapy or when used in combination with either statins or ezetimibe.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".