Nutritional interventions as modulators of the disease activity for idiopathic inflammatory myopathies: a scoping review
Bibliographic record
Abstract
Idiopathic inflammatory myopathies (IIMs) are chronic, autoimmune connective tissue diseases associated with significant morbidity and disability. Nutrients can activate the immune system and contribute to chronic low-grade inflammation (LGI). Chronic muscle inflammation leads to imbalanced pro-inflammatory and anti-inflammatory cytokines, causing inadequate nutrition, weight loss and muscle weakness during a negative cycle. Owing to its potential to modulate LGI in various diseases, the Mediterranean diet (Med Diet) has been extensively studied. This scoping review explores the nutritional implications and recommendations of the Med Diet as a treatment for immune-mediated diseases, focusing on the gaps in IIM nutritional interventions. A comprehensive literature search of the MEDLINE and EBSCO databases between September 2018 and December 2022 was performed. We identified that the Med Diet and its specific components, such as omega-3 (nω3) fatty acids, vitamin D and antioxidants, play a role in the dietary treatment of connective tissue-related autoimmune diseases. Nutritional interventions have demonstrated potential for modulating disease activity and warrant further exploration of IIMs through experimental studies. This review introduces a dietary therapeutic approach using the Med Diet and related compounds to regulate chronic inflammatory processes in IIMs. However, further clinical studies are required to evaluate the efficacy of the Med Diet in patients with IIMs. Emphasising a clinical-nutritional approach, this study encourages future research on the anti-inflammatory effects of the Med Diet on IIMs. This review highlights potential insights for managing and treating these conditions using a holistic approach.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".