Selenium Treatment Effect in Auto-Immune Hashimoto Thyroiditis in Macedonian Population
Bibliographic record
Abstract
Background: Selenium (Se), a necessary trace mineral for humans, has the highest concentration in the thyroid gland and is known of its anti-oxidant and anti-inflammatory properties. Many studies have reported that Se has a close relationship with auto-immune Hashimoto’s thyroiditis (HT), characterized by the presence of anti-thyroid peroxidase (aTPO) auto-antibodies. Methods: Five hundred thyroid patients, males and females, mean age 46 ± 19 years, with diagnosed HT, were included in the study. Euthyroid forms of HT were treated with Se only, while patients with thyroid-stimulating hormone (TSH) > 10 µIU/mL were treated with both substitutional therapy of levothyroxine and Se. Results: In around 37% of the patients treated with Se 3 × 50 µg/day with aTPO > 1,000 IU/mL, aTPO remained unchanged after 12 months, while 24.16% had aTPO < 500 IU/mL and 38.20% had aTPO between 500 and 1,000 IU/mL. Eighty-three out of 150 (55.33%) patients treated with Se 2 × 50 µg/day with aTPO between 500 and 1,000 IU/mL responded. More than half of the patients (91/172, 52.90%) with aTPO < 500 IU/mL treated with Se 50 µg/day normalized in 1 year. In hypothyroid group of patients, 12 months after treatment with levothyroxine and Se, 47.18% were responders with aTPO > 1,000 IU/mL, while 79.20% with aTPO between 500 and 1,000 IU/mL. In euthyroid group (Se only), the biggest response (30.56%) was seen in patients with the highest titer of aTPO > 1,000 IU/mL. Conclusion: Se treatment is effective in reducing the levels of aTPO in patients with HT, alone or in combination with levothyroxine. This is due to the anti-inflammatory and anti-oxidant effect of Se. Our study promotes the concept of Se treatment in patients with euthyroid or hypothyroid state, with increased titers of aTPO. J Endocrinol Metab. 2019;9(1-2):22-28 doi: https://doi.org/10.14740/jem551
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".