Evaluation of the Fracture Liaison Service within the Canadian Healthcare Setting
Bibliographic record
Abstract
Previous studies evaluating fracture liaison service (FLS) programs have found them to be cost-effective, efficient, and reduce the risk of fracture. However, few studies have evaluated the clinical effectiveness of these programs. We compared the patient populations of those referred for osteoporosis management by FLS to those referred by primary care physicians (PCP), within the Canadian healthcare system in the province of Ontario. Specifically, we investigated if a referral from FLS is similarly effective as PCP at identifying patients at risk for future osteoporotic fractures and if osteoporosis therapies have been previously initiated. A retrospective chart review of patients assessed by a single Ontario rheumatology practice affiliated with FLS between January 1, 2014, and December 31, 2017, was performed identifying two groups: those referred by FLS within Hamilton and those referred by their PCP for osteoporosis management. Fracture risk of each patient was determined using FRAX. A total of 573 patients ( n = 225 (FLS group) and n = 227 (PCP group)) were evaluated. Between the FLS and PCP groups, there were no significant differences in the absolute 10-year risk of a major osteoporotic fracture (15.6% (SD = 10.2) vs 15.3% (SD = 10.3)) and 10-year risk of hip fracture (4.7% (SD = 8.3) vs 4.7% (SD = 6.8)), respectively. 10.7% of patients referred by FLS and 40.5% of patients referred by their PCP were on osteoporosis medication prior to fracture. Our study suggests that referral from FLS is similarly effective as PCP at identifying patients at risk for future osteoporotic fractures, and clinically effective at identifying the care gap with the previous use of targeted osteoporosis therapies from referral from PCP being low and much lower in those referred by FLS. Interventional programs such as FLS can help close the treatment gap by providing appropriate care to patients that were not previously identified to be at risk for fracture by their primary care physician and initiate proper medical management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".