Effectiveness and Tolerability of Oral Administration of Low-Dose Salmon Oil to HIV Patients with HAART-Associated Dyslipidemia
Bibliographic record
Abstract
PURPOSE: To assess the effectiveness of low-dose salmon oil for the treatment of highly active antiretroviral therapy (HAART)-induced dyslipidemia in HIV-infected patients. METHOD: Randomized, open-label, parallel and crossover, multicenter study. Patients received 1 g salmon oil tid for 24 weeks (SO-24) or no additional treatment for 12 weeks and salmon oil for weeks 12 to 24 (CT-SO). The primary outcome measure was the change in triglyceride (TG) levels. RESULTS: Fifty-eight patients completed the study (26 in SO-24; 32 in CT-SO). After 12 weeks, the SO-24 group experienced a mean TG reduction of 1.1 mmol/L, compared to an increase of 0.3 mmol/L for the CT-SO group (p = .040). When CT-SO patients were crossed over to salmon oil treatment, mean TG decreased by 0.7 mmol/L (p = .052). Concomitant use of fibrates, statins, or both were reported by 16 (27.6%), 10 (17.2%), and 8 (13.8%), respectively. Multivariate analysis showed that salmon oil produced a significant decrease in TG levels independent of other lipid-lowering medications (p = .022). There were 26 predominately mild treatment-emergent (antiretroviral or salmon oil) nonserious adverse events reported by 22 (33.3%) patients. CONCLUSION: Low-dose salmon oil (3 g/day) is effective and well-tolerated in reducing TG levels in HIV-infected patients receiving HAART.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".