The relationship of hip fracture and thyroid disorders: a systematic review
Bibliographic record
Abstract
Introduction: Bone density regulation is considered one of the systems affected by thyroid hormones, leading to low bone density that can result in pathologic fractures, including hip fractures. This review aimed to update clinicians and researchers about the current data regarding the relationship between hip fractures and thyroid disorders. Methods: English papers were thoroughly searched in four main online databases of Scopus, Web of Science, PubMed, and Embase. Data extraction was done following two steps of screening/selection using distinct inclusion/exclusion criteria. This study used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist and the Newcastle-Ottawa Scale (NOS) as bias assessment. Results: In total, 19 articles were included in the research. The risk of hip fractures in women with differentiated thyroid cancer (DTC) is higher than hip fractures caused by osteoporosis. Men with hyperthyroidism and subclinical hyperthyroidism are at higher risk for hip fracture. Also, a decrease in serum thyroid stimulating hormone (TSH) may be associated with an increased risk of hip fracture. Conclusion: Reaching a consensus conclusion regarding the association between subclinical thyroid dysfunction and hip fracture is not feasible due to the heterogenicity of evidence; however, there may be a higher risk of fracture in individuals with subclinical hyperthyroidism.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".