Characterizing the Assessment and Management of Vitamin D Levels in Patients with Osteoporosis in Clinical Practice: A Chart Review Initiative
Bibliographic record
Abstract
Though vitamin D is important for bone health, little is known about the monitoring and management of vitamin D levels in patients with osteoporosis in clinical practice-a deficit this chart review initiative aimed to remedy. A total of 52 physicians completed profiles for 983 patients being treated for osteoporosis between November 2008 and April 2009. Information collected included demographics; fracture risk factors; availability and level of serum vitamin D measurements; and information on osteoporosis medications and calcium and vitamin D supplementation. Physicians also evaluated patients' current regimens and detailed proposed changes, if applicable. Nearly 85% of patients were prescribed calcium and vitamin D supplements. Serum 25-hydroxy vitamin D levels were available for 73% of patients. Of these patients, approximately 50% had levels less than 80 nmol/L, which contrasts with the 37% thought to have "unsatisfactory" vitamin D levels based on physician perceptions. Physicians felt 26% of patients would benefit from additional vitamin D supplementation. However, no changes to the osteoporosis regimen were suggested for 48% of patients perceived to have "unsatisfactory" vitamin D levels. The results underscore the importance of considering vitamin D status when looking to optimize bone health.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".