Osteoporosis Management in Patients with Hip Fracture post Fall
Bibliographic record
Abstract
Introduction: Osteoporosis increases the risk of fragility fracture. Hip fractures are associated with poor outcomes. Men are under-screened and under-treated for osteoporosis, which tends to be secondary, and men have higher mortality and worse outcomes after hip fracture than do women. This study aimed to describe patients admitted with hip fracture following minimal trauma and to explore any gender differences in calcium and vitamin D deficiency and use of osteoporosis medication before admission. Methods: A retrospective cross-sectional study included all patients admitted to Bankstown-Lidcombe Hospital with a fracture of the hip post fall, with or without surgery, from January 1, 2019, to December 31, 2019. Each patient's electronic medical record was reviewed to collect data. The data were extracted and analysed using GraphPad Prism 9.5.1. Unpaired Student's t-tests and Fisher's exact test were used in the analysis. Results: A total of 203 patients were included with a mean age of 83.5 ± 8.8 years and a range of 40 to 103 years, with over half (51.2%) aged 81 to 90 years. Fifty-nine (29.1%) were male. Of 196 patients with vitamin D levels available, 78 (39.8%) had a deficiency, including 30 of 57 (52.6%) males and 48 of 139 (34.5%) females. Males were twice as likely to be vitamin D deficient as were females on admission (OR 2.106; 95% CI 1.143 to 3.939; p = 0.0243). Of 203 patients, 39 (19.2%) were on osteoporosis treatment before admission, including 6 of 59 (10.2%) male and 33 of 144 (22.9%) female patients. Males were 2.6 times more likely to have had no osteoporosis treatment before admission than were females (OR 2.626; 95% CI 1.059 to 6.340; p = 0.0486). Conclusions: Males were more likely to have vitamin D deficiency and not be prescribed osteoporosis medication before admission in a cohort of patients admitted to the hospital with hip fracture post minimal trauma. To prevent hip fracture and resultant hospitalization, increased awareness is needed in diagnosing and managing osteoporosis in men, ideally occurring in the community.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".