Factors Associated With Pharmacologic Treatment of Osteoporosis in an Older Home Care Population
Bibliographic record
Abstract
BACKGROUND: A number of studies have shown low rates of osteoporosis treatment. Few, if any, have assessed a comprehensive range of functional and clinical correlates of treatment coverage. Our objective was to examine which sociodemographic, clinical, and functional characteristics are associated with pharmacotherapy for osteoporosis among community-based seniors. METHODS: The study sample included 48,689 home care clients aged >/= 65 years in Ontario, Canada. Treatment coverage (calcium and vitamin D and/or anti-osteoporotic drugs) was assessed in two subgroups, clients with a diagnosis of osteoporosis (without fracture) and those with a prevalent fracture. Sociodemographic, health, and functional measures available from the Resident Assessment Instrument for Home Care (RAI-HC) were assessed as correlates of treatment in multivariable logistic regression analyses. RESULTS: Approximately 59% of clients with a diagnosis of osteoporosis were receiving pharmacotherapy, compared with 27% of those with a prevalent fracture. For both subgroups, treatment coverage was significantly lower among clients with at least three chronic conditions, health instability, fewer than nine medications, functional impairment, and depressive symptoms and among those clients who were widowed. Among clients with a diagnosis of osteoporosis, treatment was positively associated with cognitive impairment and negatively associated with confinement to a wheelchair or bed. Men with a prevalent fracture were significantly less likely to receive treatment, particularly in the absence of an osteoporosis diagnosis. CONCLUSIONS: Many older adults with presumed osteoporosis in our study were not receiving drug therapy for this condition. Indicators of clinical instability and functional decline appear to represent influential factors in treatment decisions. Despite a lower likelihood of treatment among men with a prevalent fracture, this sex difference in treatment largely disappeared in the presence of an osteoporosis diagnosis.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".