Fracture Prevention in the Orthopaedic Environment: Outcomes of a Coordinator-Based Fracture Liaison Service
Bibliographic record
Abstract
BACKGROUND: Fracture liaison services focus on secondary fracture prevention by identifying patients at risk for future fracture and initiating appropriate evaluation, risk assessment, education, and therapeutic intervention. This study describes key clinical outcomes including bone mineral densitometry, physician assessment, and pharmacotherapy initiation in pharmacotherapy-naïve patients undergoing treatment for fragility fracture in a Canadian fracture liaison service. METHODS: We determined rates of post-fracture investigation and treatment for inpatients and outpatients with a fragility fracture seen in a coordinator-based fracture liaison service at an urban university trauma hospital. The program identified distal radial, proximal femoral, proximal humeral, and vertebral fragility fractures in female patients ≥40 years of age and male patients ≥50 years of age and provided education, bone mineral densitometry, inpatient consultation or outpatient specialist or primary care physician referral for bone health management, and documented patient follow-up. RESULTS: The 2,191 patients with a fragility fracture were not taking anti-osteoporosis pharmacotherapy at the time of identification (862 inpatients and 1,329 outpatients). Eighty-four percent of inpatients and 85% of outpatients completed a bone mineral densitometry as recommended. Fifty-two percent of patients with proximal femoral fracture, 29% of patients with vertebral fracture, 26% of patients with proximal humeral fracture, and 20% of patients with distal radial fracture had osteoporosis confirmed on the basis of a bone mineral densitometry T-score of ≤-2.5 at the femoral neck or L1 to L4. Eighty-five percent of inpatients and 79% of outpatients referred for bone health management were assessed by a specialist or primary care physician. Of the patients who attended their appointments, 73% of inpatients and 52% of outpatients received a prescription for anti-osteoporosis medication. CONCLUSIONS: A high rate of education, evaluation, and pharmacological treatment, if indicated, can be achieved through a coordinator-facilitated fracture liaison service program. CLINICAL RELEVANCE: Fracture prevention programs are currently engaged in establishing and modifying fracture liaison services in a quest for practical and effective models. The program described in this article exemplifies a coordinator-based model that produced good outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".