Epidemiologic changes in thyroid disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: To analyze the evolving epidemiologic trends in thyroid disease, focusing on risk factors, underlying drivers of these changes, and their implications on clinical practice and research priorities. RECENT FINDINGS: Thyroid disease remains one of the most prevalent groups of disorders globally, and the shift in its frequency and distribution is multifactorial. The prevalence of hypothyroidism increases with age, although normal thyrotropin ranges appear to be age-dependent, raising concern for potentially inappropriate levothyroxine use. Hyperthyroidism and Graves' disease continue to be predominant in reproductive-age women but exhibit a milder phenotype at diagnosis. Thyroid nodules are increasingly found in asymptomatic patients, likely from more widespread use of neck and chest imaging. Thyroid cancer incidence has risen exponentially over the years, mostly driven by overdiagnosis of low-risk tumors; however, a small rise in incidence of higher risk tumors has been noted. Obesity appears to be a risk factor for thyroid cancer occurrence and more aggressive forms of the disease. SUMMARY: Understanding epidemiologic trends in thyroid disease is crucial for guiding clinical practice and research efforts, aiming to optimize patient outcomes while preventing unnecessary and potentially harmful interventions.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".