Surgical Management of Dyslipidemia: Clinical and Experimental Evidence
Bibliographic record
Abstract
Coronary artery disease (CAD) is still a major cause of mortality in developed countries, and dyslipidemia is one of its major causes. In an attempt to reduce both mortality and morbidity from CAD, several dietary, pharmacological, and surgical approaches have been used to reduce plasma cholesterol levels. In this brief review, we summarize the evidence for cholesterol-lowering effects and safety of partial ileal bypass (PIB) procedure in both human and animal studies. The results of the Program on the Surgical Control of the Hyperlipidemias (POSCH), which involved a total of 838 subjects with myocardial infarction, are promising. A 5-year follow-up of this study revealed significant reductions of up to 27% in total cholesterol (TC) and up to 42% in low-density lipoprotein (LDL) cholesterol levels along with an increase of up to 8% in high-density lipoprotein (HDL) cholesterol levels as compared to controls. These changes were associated with other benefits such as increased HDL/TC and HDL/LDL ratios, and a significant decrease in apolipoprotein (apo) B100 and increase in apo AI levels. Similar results were also demonstrated by other studies. PIB surgery is one of the most effective methods for reduction of plasma cholesterol levels, particularly in patients with heterozygous familial hypercholesterolemia. This procedure is also applicable to treatment of sitosterolemia, a rare genetic disorder in which the absorption of plant sterols is abnormally high. Although no major complications of this method have been reported, more extensive studies are required to evaluate its long-term effects on renal and hepatic function. Similarly, long-term impact of this procedure on progression/regression of atherosclerotic lesions must be documented. Finally, indications for this procedure should be carefully considered, particularly in view of availability of other treatments of dyslipidemia.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".