Left Atrial Volume Assessed by Coronary Computed Tomography in Mid Ventricular Diastasis Predicts Adverse Events. Issue 5 (September 2016)

• Record Type: Journal Article
• Authors: Boczar, Kevin E.; Alam, Mohammed; Chow, Benjamin J.W.; Dwivedi, Girish
• Is Part Of: Journal of thoracic imaging. Volume 31:Issue 5(2016)
• Publication Date: 2016-09
• Subjects: computed tomographic coronary angiography -- left atrial volume index -- prognosis; Chest -- Radiography -- Periodicals; Chest -- Diseases -- Diagnosis -- Periodicals; 617.540757
• DOI: 10.1097/RTI.0000000000000228
• Languages: English
• ISSNs: 0883-5993

Abstract

Abstract : Purpose: Previous studies have demonstrated that left atrial (LA) volume has incremental prognostic value in predicting major adverse cardiac events (MACE). However, the predictive ability of LA volume in mid diastasis has not been investigated. We determined the incremental predictive value of LA volume indexed to body surface area (LAVi) measured in mid ventricular diastasis. Materials and Methods: A total of 96 patients with MACE (all-cause mortality and nonfatal myocardial infarction) were matched to 96 controls without adverse events on follow-up. Coronary computed tomographic angiography images were reconstructed at the 75% phase (mid ventricular diastasis). LA volumes were measured and indexed to the body surface area. The predictive value of LAVi was assessed using Cox proportional hazard models for the MACE. Results: LAVi was significantly larger ( P <0.001) in the cases with adverse clinical outcomes (63.8±2.1 mL/m 2 ) versus the controls (50.3±1.2 mL/m 2 ). In a multivariate analysis, both significant coronary artery disease (defined as >70% stenosis in at least 1 coronary artery) and LAVi emerged as significant predictors of MACE with P -values of 0.0022 and 0.0001, respectively. Conclusions: A significantly larger LAVi was associated with MACE. LAVi was an incremental predictor to traditional clinical variables for MACE. The assessment of LAVi may be considered during coronary computed tomographic angiography and could potentially be incorporated into risk stratification and decision-making strategies.