Low Bone Mineral Density and the Risk of Benign Paroxysmal Positional Vertigo
Bibliographic record
Abstract
OBJECTIVE: This study aimed to comprehensively analyze the relationship between low bone mineral density (BMD) and the risk of benign paroxysmal positional vertigo (BPPV) based on the large prospective population-based UK Biobank (UKB) cohort. STUDY DESIGN: Prospective population-based cohort study. SETTING: The UKB. METHODS: This prospective cohort study included UKB participants recruited between 2006 and 2010 who had information on BMD and did not have BPPV before being diagnosed with low BMD. Univariable and multivariable logistic regression models were constructed to assess the association between low BMD (overall low BMD, osteopenia, and osteoporosis) and BPPV. We further conducted sex and age subgroup analysis, respectively. Finally, the effects of antiosteoporosis and female sex hormone medications on BPPV in participants with osteoporosis were evaluated. RESULTS: In total, 484,303 participants were included in the final analysis, and 985 developed BPPV after a maximum follow-up period of 15 years. Osteoporosis was associated with a higher risk of BPPV (odds ratio [OR] = 1.37, P = .0094), whereas osteopenia was not. Subgroup analyses suggested that the association between osteoporosis and BPPV was significant only in elderly females (≥60 years, OR = 1.51, P = .0007). However, no association was observed between antiosteoporosis or female sex hormone medications and BPPV in the participants with osteoporosis. CONCLUSION: Osteoporosis was associated with a higher risk of developing general BPPV, especially in females aged ≥ 60 years old, whereas osteopenia was not associated with BPPV.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".