RESUMEN
BACKGROUND: Coronary embolism (CE) is an uncommon cause of non-atherosclerotic acute myocardial infarction (AMI). Although atrial fibrillation (AF) is the main cause of CE, evidence of clinical, biochemical, echocardiographic, angiographic findings and outcomes of AF CE is lacking. METHODS: We retrospectively analyzed 85 consecutive patients with CE that was diagnosed based on criteria encompassing clinical, angiographic and diagnostic imaging findings. We classified patients according to AF CE or non-AF CE. RESULTS: Forty-five patients presented with AF CE (53%). Patients with AF CE were older (76 ± 12 vs. 63 ± 14 years; p < 0.001) and had more often chronic kidney disease (24% vs. 5%; p = 0.01). AF CE had lower estimated glomerular filtration rate at admission (59 ± 18 vs. 77 ± 16 ml/min/1.73 m2; p < 0.001) and higher brain natriuretic peptide levels (512 ± 417 vs. 210 ± 479 pg/ml; p = 0.02). Coronary arteriography revealed a higher incidence of coronary artery obstruction in the AF CE group (73% vs. 38%; p = 0.001) without differences in interventional management. The AF CE group showed higher left atrial volume index (LAVI) (42 ± 15 vs. 25 ± 12 ml/m2; p < 0.001) and showed lower left atrium ejection fraction (LAEF) (32 ± 17 vs. 49 ± 17%; p = 0.001). In the multivariable analysis AF CE (OR 10 [95% CI 1.04-95; p = 0.046]) and LAEF (OR 0.94 [95% CI 0.88-0.99; p = 0.02]) were associated with worse in-hospital outcomes. Moreover, in the multivariable analysis, prior stroke (OR 12.5 [95% CI 1.1-137; p = 0.04]) and LAVI (OR 1.1 [95% CI 1.03-1.14; p = 0.003]) were independently associated with worse long-term outcomes. CONCLUSION: AF CE has specific characteristics compared to non-AF-CE and it is associated with more in-hospital events. Furthermore, atrial cardiopathy is associated with worse in-hospital and long-term outcomes in this setting.
RESUMEN
AIMS: Late gadolinium enhancement (LGE) is frequently found in patients with dilated cardiomyopathy (DCM); there is little information about its frequency and distribution pattern according to the underlying genetic substrate. We sought to describe LGE patterns according to genotypes and to analyse the risk of major ventricular arrhythmias (MVA) according to patterns. METHODS AND RESULTS: Cardiac magnetic resonance findings and LGE distribution according to genetics were performed in a cohort of 600 DCM patients followed at 20 Spanish centres. After exclusion of individuals with multiple causative gene variants or with variants in infrequent DCM-causing genes, 577 patients (34% females, mean age 53.5 years, left ventricular ejection fraction 36.9 ± 13.9%) conformed to the final cohort. A causative genetic variant was identified in 219 (38%) patients, and 147 (25.5%) had LGE. Significant differences were found comparing LGE patterns between genes (P < 0.001). LGE was absent or rare in patients with variants in TNNT2, RBM20, and MYH7 (0, 5, and 20%, respectively). Patients with variants in DMD, DSP, and FLNC showed a predominance of LGE subepicardial patterns (50, 41, and 18%, respectively), whereas patients with variants in TTN, BAG3, LMNA, and MYBPC3 showed unspecific LGE patterns. The genetic yield differed according to LGE patterns. Patients with subepicardial, lineal midwall, transmural, and right ventricular insertion points or with combinations of LGE patterns showed an increased risk of MVA compared with patients without LGE. CONCLUSION: LGE patterns in DCM have a specific distribution according to the affected gene. Certain LGE patterns are associated with an increased risk of MVA and with an increased yield of genetic testing.
