Efficacy and safety of chitosan HEP-40 in the management of hypercholesterolemia: a randomized, multicenter, placebo-controlled trial.
Bibliographic record
Abstract
UNLABELLED: Hypercholesterolemia is an important risk factor for cardiovascular disease (CVD). OBJECTIVE: To compare the efficacy of a 12-week treatment regimen with HEP-40 low-molecular weight chitosan given at daily doses of 1,200 mg, 1,600 mg, and 2,400 mg in reducing serum low-density lipoprotein cholesterol (LDL-C) in patients with low-to-moderate hypercholesterolemia. DESIGN: The study was a 16-week, multicenter, placebo-controlled, randomized study. Eligible patients were treatment-naive for lipid-lowering medications. Patients were randomly assigned to HEP-40 at the following doses: 400 mg three times daily, 800 mg twice daily, 800 mg three times daily, 2,400 mg once daily, or placebo for 12 weeks. The main outcome measure was the percent change in LDL-C after four weeks of treatment. RESULTS: Out of 283 patients screened, 105 (37.1%) fulfilled the inclusion criteria and 95 (90.4%) completed the study. The mean (SD) age was 53 (11) years and 62.3 percent were male. The majority of patients (82.9%) were at low 10-year risk for CVD. The results showed an overall treatment effect (p=0.040) with the highest difference from the placebo group observed for the HEP-40 2,400-mg once daily group (-16.9%, p=0.002), followed by 400 mg three times daily (-11.1%, p=0.054), 800 mg three times daily (-9.7%, p=0.065), and 800 mg twice daily (-8.7%, p=0.101). There were 29 predominantly mild adverse events reported by 24 (23%) patients related to the study treatment, most frequently constipation (3.0%) and diarrhea (3.0%). CONCLUSION: HEP-40 low-molecular weight chitosan, although not as effective as statins, is efficacious and safe in lowering LDL-C concentrations in treatment-naive patients with low-to-moderate hypercholesterolemia.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".