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5 Structural predictors of atrial fibrillation in hypertrophic cardiomyopathy using cardiac magnetic resonance imaging
  1. A Ghosh Dastidar1,2,
  2. E De Garate1,
  3. P Singhal2,
  4. J Rodrigues1,3,
  5. A Baritussio1,
  6. A Scatteia1,
  7. A Nightingale1,2,
  8. AG Stuart1,2,
  9. C Bucciarelli-Ducci1,2
  1. 1NIHR Bristol Cardiovascular Biomedical Research Unit, Bristol Heart Institute, UK
  2. 2School of Clinical Sciences, Faculty of Health Sciences, University of Bristol, UK
  3. 3School of Physiology, Pharmacology and Neuroscience, Faculty of Biomedical Sciences, University of Bristol University of Bristol, UK


Background Atrial fibrillation (AF) is the most common sustained arrhythmia in hypertrophic cardiomyopathy (HCM) and is associated with major adverse cardiovascular events. Cardiac magnetic resonance (CMR) with its superior tissue characterisation property is currently the imaging modality of choice for HCM.

Aims To identify the structural predictors of AF in HCM using CMR.

Methods 114 consecutive HCM patients were identified after reviewing approximately 3,100 CMR scans from our registry (Jan 2014 to Mar 2015). Comprehensive CMR protocol was used including cines, early and late gadolinium enhancement imaging. The diagnosis of HCM was based on left ventricular (LV) maximum wall thickness ≥15 mm (or 13–14 mm in the presence of familial history and/or ECG changes), in the absence of other cardiac/systemic disorders producing a similar degree of hypertrophy. Clinical notes were evaluated to identify a documented episode of AF. Univariate and multivariate logistic regression analyses were performed to determine the CMR imaging predictors of AF in HCM.

Results The final study sample consisted of 104 patients with HCM with median age 60years (IQR = 54–70) and 70% male, (10 patients excluded due to uncertain/overlapping diagnosis). 70% had non-apical HCM; the remainder 30% apical HCM. 16% (n = 17) had a documented episode of atrial fibrillation. The univariate predictors of AF included left atrial volume and the ratio of left atrial volume to LV end systolic volume whereas in the multivariate model the ratio of left atrial volume to LV end systolic volume remained the only significant predictor (p = 0.034, OR = 2.236, CI = 1.06–4.70) (Table 1).

Conclusion Our study suggests that the ratio of left atrial volume to LV end systolic volume is the best predictor of AF in HCM. The simple CMR derived ratio may have potential role for AF risk stratification in HCM.

Abstract 5 Table 1

Predictors of AF in HCM

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