Oral supplementation with omega-3 fatty acids and inflammation markers in patients with chronic kidney disease in hemodialysis
Bibliographic record
Abstract
Chronic kidney disease (CKD) is an increasingly common public health problem that increases the risk of death because of cardiovascular complications by 2–3 times compared with the general population. This research concerns a prospective, randomized, double-blind study in patients with CKD undergoing hemodialysis. The participants were assigned to 1 of 2 groups: the study group (group A; 46 patients) received 4 capsules (2.4 g) of omega-3 fatty acids daily during the 12-week intervention, while patients in the control group (group B; 47 patients) received 4 capsules of paraffin oil. The patients’ general characteristics, nutritional indicators, renal disease markers and inflammatory markers (C-reactive protein, interleukin (IL)-6, IL-10, and tumour necrosis factor alpha (TNF-α)) were evaluated. No differences were found between the general characteristics of the patients (P < 0.05), and no differences were shown in the nutritional indicators and markers of kidney disease (P < 0.05). Patients in group A showed significant decreases in levels of C-reactive protein, IL-6, TNF-α, and the IL-10/IL-6 ratio after 12 weeks of supplementation (P < 0.05). Patients in group B did not show any significant changes in concentrations of inflammatory markers during the intervention (P < 0.05). In conclusion, oral supplementation with omega-3 fatty acids produces a significant decrease in the concentrations of inflammation markers in patients with chronic kidney disease on hemodialysis. Novelty Oral supplementation with omega-3 fatty acids produced significant decreases in the concentrations of inflammation markers. This supplementation could be given to patients with uremic syndrome and coronary heart disease to reduce cardiovascular risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".