Factors associated with serum thyroglobulin levels in a population living in Belarus
Bibliographic record
Abstract
OBJECTIVE: Serum thyroglobulin (Tg) has been associated with a number of thyroid disorders and has been proposed as an indicator of iodine deficiency in a population. However, few studies have addressed the epidemiology of Tg in a population-based setting or in the context of exposure to radioactive iodine-131 (I-131). Our objective was to evaluate baseline levels of Tg in relation to sociodemographic characteristics, iodine status and thyroid function for individuals exposed to I-131. DESIGN: A population-based cohort assembled in Belarus following the Chornobyl accident provided demographic factors, clinical data and physiological measurements. PARTICIPANTS: Our analytical sample included 10,344 subjects of whom 7890 had no thyroid disease and 2454 had evidence of structural or functional thyroid abnormality. MEASUREMENTS: Standardized assays were used to measure serum Tg, urinary iodine, TSH and antibodies to Tg and thyroid peroxidase. Ultrasound was used to assess the presence of nodules and estimate thyroid volume. RESULTS: In the fully adjusted model, percent change in Tg was significantly increased among females, smokers and subjects of older age and Tg increased with decreasing urinary iodine concentration, increasing serum TSH and increasing thyroid volume (P-values for trend <0·0001), and presence of thyroid nodules (P < 0·05). We found a complex interaction between region of residence, rural/urban living, presence/absence of thyroid abnormalities and serum Tg (P < 0·0001). CONCLUSIONS: In residents of Belarus, serum Tg is significantly related to presence of thyroid abnormalities as well as indicators of thyroid function and iodine deficiency and, therefore, could be used to characterize the iodine status and thyroid function of individuals in the context of epidemiological study.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".