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  • Title: Association of computed tomography-derived left ventricular size with major cardiovascular events in the general population: the Heinz Nixdorf recall study.
    Author: Dykun I, Geisel MH, Kälsch H, Lehmann N, Bauer M, Moebus S, Jöckel KH, Möhlenkamp S, Erbel R, Mahabadi AA.
    Journal: Atherosclerosis; 2015 May; 240(1):46-52. PubMed ID: 25746377.
    Abstract:
    OBJECTIVE: To investigate the relationship between LV size as determined by non-contrast enhanced cardiac CT with incident cardiovascular disease in the general population free of clinical cardiovascular disease. METHODS: LV axial area was quantified from non-contrast CT in axial, end-diastolic images at a mid-ventricular slice in participants from the population-based Heinz Nixdorf recall study, free of cardiovascular disease (n=3926, 59±8years, 53%female). LV size index (LVI) was defined as the quotient of LV area and body surface area. Major CV events (coronary events, stroke, CV death) were assessed during follow-up. Association of LVI with events was assessed using Cox regression analysis in unadjusted and multivariable adjusted models. RESULTS: During 8.0±1.5years of follow-up, 219 subjects developed a major CV event. Those with events had larger LVI at baseline (2258±352 vs. 2149±276 mm2/m2, p<0.0001). In univariate analysis, increase of LVI by 1 standard deviation was associated with 40% higher risk of events (HR(95%CI):1.41(1.26-1.59), p<0.0001). Associations remained statistically significant after adjustment for CV risk factors (1.24(1.10-1.40), p=0.0007) and when further adjusting for CAC (1.21(1.07-1.37), p=0.003). There was a trend towards stronger association for subjects with low CAC-score (CAC<100:1.41(1.16-1.71), p=0.0005, CAC≥100:1.24(1.06-1.44), p=0.006) in univariate analysis which persisted after multivariable adjustment (CAC<100: 1.41(1.14-1.73), p=0.001, CAC≥100: 1.12(0.96-1.31), p=0.16). CONCLUSION: CT-derived LV size is associated with incident major CV events independent of traditional risk factors and CAC-score in a population-based cohort and may improve the prediction of hard events especially in subjects with low CAC-scores.
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