Omega-3 in The Treatment of Mood and Sleep Disorders Induced by Hormone Therapy in Women with Breast Cancer: A Randomized, Double-Blinded, Placebo-Controlled Clinical Trial
Bibliographic record
Abstract
Abstract Purpose This study was performed to investigate the effect of omega-3 on the treatment of mood and sleep disorder induced by menopausal complications due to hormone therapy in patients with breast cancer. Methods A placebo, double-blind and controlled trial was designed in oncology-hematology outpatient’s clinic of Omid Hospital, Isfahan, Iran. First, sixty patients were screened by hospital anxiety and depression scale (HADS) for any baseline mood disorders and then divided into either intervention group who had received 2 grams’ omega-3 daily for 4 weeks or identical placebo. Then, the patients were considered to assess by center for epidemiological studies-depression scale (CES-D), profile of mood states (POMS), and Pittsburgh sleep quality index (PSQI) questionnaires at the baseline and after 4-week follow-up. Results Findings showed that the mean scores of CES-D (P = 0.002), POMS (P = 0.03), and PSQI (P = 0.04) were significantly lower in the intervention group than the control group. In the intervention group, mean scores of CES-D (P <0.001), POMS (P <0.001), and PSQI (P = 0.003) were significantly lower in post-intervention than pre-intervention. Mean changes in scores of CES-D (P = 0.01), POMS (P = 0.001), and PSQI (P = 0.02) were significantly higher in the intervention group than the control group. Conclusion Our findings revealed that omega-3 supplementation have the potential to reduce mood disorders as well as to improve sleep quality in terms of subjective sleep quality, delay in falling asleep, sleep delay, and sleep disturbance in patients with breast cancer.
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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) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".