Fracture risk of patients suffering from dizziness: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Dizziness is known to be associated with the risk of falls. However, there is not much evidence for the increase of fractures caused by dizziness. OBJECTIVES: The aim of the study was to investigate whether the symptom of dizziness is associated with an increased fracture rate. METHODS: We performed a retrospective cohort study using a population-based administrative database in the Province of Quebec, Canada. A cohort of n = 2442 patients with at least one diagnosis of dizziness was compared to n = 16,125 unexposed patients. The main outcome measure was any kind of first fracture after the index date of dizziness. RESULTS: Analysis revealed a moderate effect of dizziness as an independent contributing factor to fractures (adjusted hazard ratio (HR) 1.26, 95% confidence interval 1.03 to 1.55). A fracture in the year before the index date was highly associated with the incidence of a subsequent fracture (HR 2.69, 2.09 to 3.47), and fractures were less frequent in women (HR 0.70, 0.60-0.82). Analysis further revealed that dizziness (HR 1.31, 1.05-1.64) and prior fractures (HR 2.41, 1.81-3.22) were associated with non-osteoporotic fractures, which were also less frequent in women (HR 0.59, 0.50-0.71). The incidence of fractures in sites typical for osteoporosis correlated with a precedent fracture (HR 3.91, 2.31-6.63), but not with dizziness (HR 1.10, 0.69-1.75). CONCLUSION: Besides the 'typical' elderly female patient being at risk of osteoporotic fractures, male patients suffering from dizziness should be carefully evaluated, and prevention strategies should be considered to minimise their risk of suffering non-osteoporotic fractures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".