The interplay between vitamin C and thyroid
Bibliographic record
Abstract
INTRODUCTION: Vitamin C (ascorbic acid) is a water-soluble vitamin, that plays a key role in the prevention and treatment of scurvy. As vitamin C is an antioxidant and thyroid function may be affected and may affect vitamin C levels, for the first time, we aimed to provide a detailed review of all human studies evaluating the different roles of vitamin C in the thyroid gland. Thyroid cancers, goitre, Graves' disease and other causes of hyperthyroidism and hypothyroidism were the conditions discussed in this study. Furthermore, vitamin C addition to other medications such as levothyroxine was also reviewed. METHODS: In this study, we reviewed the relevant literature regarding the association between vitamin C and thyroid diseases using original studies from PubMed, Scopus, Embase, and Web of Science. RESULTS: In this review, we found anti-cancer effects for intravenous (IV) administration of vitamin C in addition to the beneficial effects of using it in combination with radiotherapy and chemotherapy. As autoimmune diseases affect some antioxidant markers, some studies reported a significant difference in blood vitamin C levels in patients with autoimmune thyroid diseases such as Graves' disease. Despite many studies evaluating the effects of IV administration of vitamin C in mentioned diseases, there is a lack of evidence for oral consumption of vitamin C. CONCLUSIONS: To conclude, there is a lack of evidence, especially clinical trials, for the therapeutic effects of vitamin C on thyroid diseases; however, promising results were reported in some studies in the literature.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".