CONTEXT: Abdominal aortic calcification (AAC) is a common finding in patients with atherosclerosis. OBJECTIVE: The aim of this study was to demonstrate the incremental value of AAC in predicting long term cardiovascular (CV) outcome by conducting a meta-analysis of observational studies. DATA SOURCES: MEDLINE and Cochrane databases. STUDY SELECTION: Longitudinal studies with at least 2 years of follow-up, reporting the influence of AAC on CV outcome of general population patients. DATA EXTRACTION: Four separate end points-coronary events, cerebrovascular events, all CV events and CV related death-were tested for their relationship with AAC at baseline, using weighted random effects meta-analysis. Heterogeneity was calculated using Q and I(2) statistic tests. Publication bias was assessed by funnel plot symmetry and trim and fill methods. The importance of calcium quantification was also explored (sensitivity analysis). RESULTS: 10 studies were included. An increased relative risk (RR) was found for all end points: for coronary events (five studies, n=11250) 1.81 (95% CI 1.54 to 2.14); for cerebrovascular events (four studies, n=9736) 1.37 (1.22 to 3.54); for all CV events (four studies, n=4960) 1.64 (1.24 to 2.17); and for CV death (three studies, n=4986) 1.72 (1.03 to 2.86). Analysis of studies presenting results in categories (no/minimal, moderate and severe calcification) revealed a stepwise increase in the RR for all end points. Significant heterogeneity was found in the included studies. Sources of heterogeneity were identified in the publication date, duration of follow-up, and mean age and gender differences in the included patient cohorts. CONCLUSION: Existing data suggest that AAC is a strong predictor of CV related events or death in the general population. The predictive impact is greater in more calcified aortas. The generalisability of the meta-analysis is limited by heterogeneity in the coronary events, all CV events and CV death end points.
CONTEXT: Abdominal aortic calcification (AAC) is a common finding in patients with atherosclerosis. OBJECTIVE: The aim of this study was to demonstrate the incremental value of AAC in predicting long term cardiovascular (CV) outcome by conducting a meta-analysis of observational studies. DATA SOURCES: MEDLINE and Cochrane databases. STUDY SELECTION: Longitudinal studies with at least 2 years of follow-up, reporting the influence of AAC on CV outcome of general population patients. DATA EXTRACTION: Four separate end points-coronary events, cerebrovascular events, all CV events and CV related death-were tested for their relationship with AAC at baseline, using weighted random effects meta-analysis. Heterogeneity was calculated using Q and I(2) statistic tests. Publication bias was assessed by funnel plot symmetry and trim and fill methods. The importance of calcium quantification was also explored (sensitivity analysis). RESULTS: 10 studies were included. An increased relative risk (RR) was found for all end points: for coronary events (five studies, n=11250) 1.81 (95% CI 1.54 to 2.14); for cerebrovascular events (four studies, n=9736) 1.37 (1.22 to 3.54); for all CV events (four studies, n=4960) 1.64 (1.24 to 2.17); and for CV death (three studies, n=4986) 1.72 (1.03 to 2.86). Analysis of studies presenting results in categories (no/minimal, moderate and severe calcification) revealed a stepwise increase in the RR for all end points. Significant heterogeneity was found in the included studies. Sources of heterogeneity were identified in the publication date, duration of follow-up, and mean age and gender differences in the included patient cohorts. CONCLUSION: Existing data suggest that AAC is a strong predictor of CV related events or death in the general population. The predictive impact is greater in more calcified aortas. The generalisability of the meta-analysis is limited by heterogeneity in the coronary events, all CV events and CV death end points.
Authors: Tasnim F Imran; Yash Patel; R Curtis Ellison; J Jeffrey Carr; Donna K Arnett; James S Pankow; Gerardo Heiss; Steven C Hunt; J Michael Gaziano; Luc Djoussé Journal: Arterioscler Thromb Vasc Biol Date: 2016-04-21 Impact factor: 8.311
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Authors: Michael H Criqui; Julie O Denenberg; Robyn L McClelland; Matthew A Allison; Joachim H Ix; Alan Guerci; Kevin P Cohoon; Preethi Srikanthan; Karol E Watson; Nathan D Wong Journal: Arterioscler Thromb Vasc Biol Date: 2014-05-08 Impact factor: 8.311