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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.

Musa Sani DanazumiNicol LightbodyGordana Dermody
Published in: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA (2024)
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. Review registration: PROSPERO-CRD42021266408.
Keyphrases
  • randomized controlled trial
  • mental health
  • case control
  • physical activity
  • systematic review
  • clinical trial
  • machine learning
  • high intensity
  • deep learning
  • middle aged