Effectiveness of fracture liaison service in reducing the risk of secondary fragility fractures in adults aged 50 and older: a systematic review and meta-analysis
Bibliographic record
Abstract
To determine and appraise the certainty of fracture liaison service (FLS) in reducing the risk of secondary fragility fractures in older adults aged ≥ 50 years and to examine the nature of the FLS and the roles of various disciplines involved in the delivery of the FLS. Medline, EMBASE, PubMed, CINAHL, SCOPUS, and The Cochrane Library were searched from January 1st, 2010, to May 31st, 2022. Two reviewers independently extracted data. The risk of bias was evaluated using the Newcastle–Ottawa Scale for cohort studies and the PEDro scale for randomized trials, while the GRADE approach established the certainty of the evidence. Thirty-seven studies were identified of which 34 (91.9%) were rated as having a low risk of bias and 22 (59.5%) were meta-analyzed. Clinically important low certainty evidence at 1 year (RR 0.26, CI 0.13 to 0.52, 6 pooled studies) and moderate certainty evidence at ≥ 2 years (RR 0.68, CI 0.55 to 0.83, 13 pooled studies) indicate that the risk of secondary fragility fracture was lower in the FLS intervention compared to the non-FLS intervention. Sensitivity analyses with no observed heterogeneity confirmed these findings. This review found clinically important moderate certainty evidence showing that the risk of secondary fragility fracture was lower in the FLS intervention at ≥ 2 years. More high-quality studies in this field could improve the certainty of the evidence.
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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 | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".