NUTRITIONAL INTERVENTIONS FOR ENDOCRINE DISORDER MANAGEMENT: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
BackgroundEndocrine disorders such as diabetes, thyroid dysfunction, and metabolic syndrome are major contributors to global morbidity, often requiring lifelong management. Emerging evidence suggests that nutritional interventions may positively influence hormonal regulation and metabolic outcomes in these conditions. However, current literature is fragmented, and no comprehensive synthesis has been conducted to evaluate the breadth and quality of this evidence. ObjectiveThis systematic review aims to evaluate the effectiveness of dietary and nutritional interventions in improving clinical and biochemical outcomes in patients with endocrine disorders. MethodsA systematic review was conducted in accordance with PRISMA guidelines. Four electronic databases—PubMed, Scopus, Web of Science, and Cochrane Library—were searched for studies published in the last five years. Inclusion criteria encompassed randomized controlled trials, cohort studies, and narrative reviews examining dietary interventions in endocrine disorders. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale. Due to heterogeneity in outcomes and study designs, a qualitative synthesis was performed. ResultsEight studies met the inclusion criteria. Nutritional strategies ranged from caloric restriction and macronutrient modulation to therapeutic dietary support in oncology and perinatal care. Key findings included the identification of APOC1 as a biomarker responsive to acute dietary changes, and associations between maternal diet and offspring endocrine health. Most studies supported the role of nutrition in improving metabolic parameters, though methodological variability limited direct comparison. Risk of bias was moderate to high in several studies. ConclusionNutritional interventions appear to have significant potential in enhancing outcomes for patients with endocrine disorders. However, current evidence is limited by heterogeneity and moderate methodological quality. Further high-quality, large-scale clinical trials are needed to establish standardized nutritional protocols and evaluate long-term benefits.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".