The Association Between Thyroid Dysfunction and the Risk of Fractures: A Systematic Review
Bibliographic record
Abstract
Thyroid hormones are crucial regulators of bone metabolism. While overt thyroid dysfunction is a recognized risk factor for osteoporosis, the association between subclinical thyroid dysfunction, variations within the euthyroid range, and fracture risk remains complex and less clearly defined. This systematic review aimed to comprehensively evaluate the association between various states of thyroid dysfunction and the risk of incident fractures. A systematic literature search was conducted in accordance with PRISMA guidelines across PubMed, Web of Science, SCOPUS, and ScienceDirect. Studies investigating the association between thyroid dysfunction (overt and subclinical hypo-/hyperthyroidism, euthyroid variations, autoimmune thyroiditis, and thyroid cancer) and fracture risk were included. Two independent reviewers performed study selection, data extraction, and risk of bias assessment using the Newcastle-Ottawa Scale. Thirteen studies met the inclusion criteria. The evidence consistently demonstrated that subclinical hyper-thyroidism and lower thyroid-stimulating hormone (TSH) levels, even within the euthyroid range, were associated with an increased risk of fractures and impaired bone microarchitecture. Several large cohort studies found a lower fracture risk in patients with thyroid cancer, particularly those with postoperative hypoparathyroidism, suggesting a protective effect from intensive calcium and vitamin D supplementation and a low bone turnover state. The relationship between thyroid function and fracture risk is multifaceted. Subclinical hyperthyroidism and low TSH were significant, independent risk factors. The association extends into the euthyroid range, influenced by thyroid hormone sensitivity and autoimmunity. The reduced fracture risk in thyroid cancer patients highlights the critical role of iatrogenic factors and proactive management.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".