A Missed Opportunity in Bone Health: Vitamin D and Calcium Use in Elderly Femoral Neck Fracture Patients Following Arthroplasty
Bibliographic record
Abstract
INTRODUCTION: Introduction: Adequate calcium and vitamin D from diet and supplementation is recommended for elderly hip fracture patients. Using data from the multinational hip fracture arthroplasty trial (HEALTH), we determined the proportion of patients who consistently took vitamin D and calcium and which characteristics/prescribing practices were associated with consistency of supplement use. METHODS: HEALTH is a multicenter randomized trial of elderly hip fracture patients treated with hemi-arthroplasty and total hip arthroplasty. Patients were categorized as consistent users, inconsistent users, or nonusers of calcium and vitamin D. We used multinomial regression to determine the characteristics associated with calcium and vitamin D use. RESULTS: 603 HEALTH participants were included in the analysis. 34.7% of patients never took vitamin D within 12 months after surgery, 26.2% took vitamin D inconsistently, and 39.1% took vitamin D consistently. 36.0% of patients never took calcium within 12 months after surgery, 28.4% took calcium inconsistently, and 35.7% took calcium consistently. There was great variation in prescribed/recommended doses. Compared to nonusers, consistent users of the supplements were more likely to be female, North American, prescribed/recommended vitamin D and/or calcium postoperatively, and presented to a facility with comprehensive fragility fracture protocols. CONCLUSIONS: A low proportion of elderly hip fracture patients are consistently taking vitamin D and calcium, which may contribute to poorer bone health. Surgeons should be educated to prescribe/ recommend vitamin D and calcium, institutions should develop comprehensive fragility fracture protocols and patient education strategies to ensure that patients with osteoporosis receive bone health management beyond fracture care.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".