Abdominal aortic calcification, bone mineral density and fractures: A systematic review and meta-Analysis protocol

Alexander J. Rodríguez, Kevin Leow, Pawel Szulc, David Scott, Peter Ebeling, Marc Sim, Germaine Wong, Wai H. Lim, John T. Schousboe, Douglas P. Kiel, Richard L. Prince, Joshua R. Lewis

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)


Introduction Abdominal aortic calcification (AAC) is associated with low bone mass and increased fracture risk. Two previous meta-Analyses have investigated the association between AAC and fracture. However, these meta-Analyses only identified articles until December 2016, undertook limited searches and did not explore potential sources of between-study heterogeneity. We aim to undertake a sensitive and comprehensive assessment of the relationship between AAC, bone mineral density (BMD) as well as prevalent and incident fractures. Methods We will search MEDLINE, EMBASE, Web of Science core collection and Google Scholar (top 200 articles sorted by relevance) from their inception to 1 June 2018. Reference lists of included studies and previous systematic reviews will be hand searched for additional eligible studies. Retrospective and prospective cohort studies (cross-sectional, case-control and longitudinal) reporting the association between AAC, BMD and fracture at any site will be included. At least two investigators will independently: (A) evaluate study eligibility and extract data, with a third investigator to adjudicate when discrepancies occur, (B) assess study quality by the Newcastle-Ottawa Scale for each cohort/study. The meta-Analysis will be reported in adherence to the Meta-Analysis of Observational Studies in Epidemiology criteria. AAC will be grouped as either: (1) AAC present or absent, (2) AAC categorised as â € low' (referent-lowest reported group) versus â € high' (all other groups) or (3) dose-response when AAC was assessed in ≥3 groups. Where primary event data were reported in individual studies, pooled risk differences and risk ratios with 95% CI will be calculated, from which, a summary estimate will be determined using DerSimonian-Laird random effects models. For the AAC and BMD pooled analyses, estimates will be expressed as standardised mean difference with 95% CI. We will examine the likelihood of publication bias and where possible, investigate potential reasons for between-study heterogeneity using subgroup analyses and meta-regression. Ethics and dissemination The study will be submitted to a peer-reviewed journal and disseminated via research presentations. PROSPERO registration number CRD42018088019.

Original languageEnglish
Article numbere026232
Number of pages5
JournalBMJ Open
Issue number4
Publication statusPublished - 1 Apr 2019


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