scholarly journals Evaluation of Atrial Electromechanical Delay to Predict Atrial Fibrillation in Hemodialysis Patients

Medicina ◽  
2018 ◽  
Vol 54 (4) ◽  
pp. 58 ◽  
Author(s):  
Hakan Gunes ◽  
Abdullah Sokmen ◽  
Hakki Kaya ◽  
Ozkan Gungor ◽  
Murat Kerkutluoglu ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Odds Ratio ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Tissue Doppler ◽  
Hemodialysis Patients ◽  
Multivariate Logistic Regression Model ◽  
Electromechanical Delay ◽  
Holter Ecg ◽  
Atrial Electromechanical Delay

Background and objective: Prevalence of atrial fibrillation is higher in hemodialysis patients as compared to the general population. Atrial electromechanical delay is known as a significant predictor of atrial fibrillation. In this study, we aimed to reveal the relationship between atrial electromechanical delay and attacks of atrial fibrillation. Materials and methods: The study included 77 hemodialysis patients over 18 years of age giving written consent to participate in the study. The patients were divided into two groups based on the results of 24-h Holter Electrocardiogram (Holter ECG) as the ones having attacks of atrial fibrillation and the others without any attack of atrial fibrillation. Standard echocardiographic measurements were taken from all patients. Additionally, atrial conduction times were measured by tissue Doppler technique and atrial electromechanical delays were calculated. Results: Intra- and interatrial electromechanical delay were found as significantly lengthened in the group of patients with attacks of atrial fibrillation (p = 0.03 and p < 0.001 respectively). The optimal cut-off time for interatrial electromechanical delay to predict atrial fibrillation was >21 ms with a specificity of 79.3% and a sensitivity of 73.7% (area under the curve 0.820; 95% confidence interval (CI), 0.716–0.898). In the multivariate logistic regression model, interatrial electromechanical delay (odds ratio = 1.230; 95% CI, 1.104–1.370; p < 0.001) and hypertension (odds ratio = 4.525; 95% CI, 1.042–19.651; p = 0.044) were also associated with atrial fibrillation after adjustment for variables found to be statistically significant in univariate analysis and correlated with interatrial electromechanical delay. Conclusions: Interatrial electromechanical delay is independently related with the attacks of atrial fibrillation detected on Holter ECG records in hemodialysis patients.

scholarly journals Usefulness of Tissue Doppler-derived Atrial Electromechanical Delay for Identifying Patients with Paroxysmal Atrial Fibrillation

2020 ◽  
Author(s):  
Kanako Akamatsu ◽  
Takahide Ito ◽  
Masatoshi Miyamura ◽  
Yumiko Kanzaki ◽  
Koichi Sohmiya ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Left Atrial ◽  
Left Atrial Volume ◽  
Tissue Doppler ◽  
P Wave ◽  
Volume Index ◽  
Atrial Volume ◽  
Electromechanical Delay ◽  
Left Atrial Volume Index ◽  
Atrial Electromechanical Delay

Abstract Background: Tissue Doppler imaging (TDI)-derived atrial electromechanical delay (AEMD), has been reported to be useful for predicting development of atrial fibrillation (AF). However, its usefulness remains unknown when analyzed along with patients seemingly at high-risk for AF as controls. From this standpoint, we investigated whether AEMD would be of use for identifying patients with paroxysmal AF (PAF). Methods: We analyzed TDI recordings to obtain AEMD in 73 PAF patients. Thirty-nine patients with multiple cardiovascular risk factors (MRFs) but without history of AF and 61 healthy individuals served as disease and healthy controls, respectively. AEMD was defined as the time-interval between the electrocardiogram P-wave and the beginning of the spectral TDI-derived A’ for the septal (septal EMD) and lateral (lateral EMD) sides of the mitral annulus. Results: There was no significant difference in the left atrial volume index between PAF patients and disease controls (28 ± 5 mL/m2 vs. 27 ± 5 mL/m2). PAF patients had longer AEMD, particularly for the lateral EMD (78 ± 26 ms), compared with disease (62 ± 21 ms, P = 0.003) and healthy (53 ± 24 ms, P <0.001) controls. Multivariate logistic regression analysis revealed that the lateral EMD (OR 1.42, 95%CI 1.16 – 1.75, P <0.001), along with the left atrial volume index (OR 2.86, 95%CI 1.70 – 4.80, P <0.001), was one of the significant independent associates of identifying PAF　patients. Conclusions: According to our data, analyzed along with MRFs patients, AEMD seems to be a useful index of identifying patients at risk for AF.

scholarly journals Usefulness of Tissue Doppler-derived Atrial Electromechanical Delay for Identifying Patients with Paroxysmal Atrial Fibrillation

2020 ◽  
Author(s):  
Kanako Akamatsu ◽  
Takahide Ito ◽  
Masatoshi Miyamura ◽  
Yumiko Kanzaki ◽  
Koichi Sohmiya ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Paroxysmal Atrial Fibrillation ◽  
Left Atrial ◽  
Left Atrial Volume ◽  
Tissue Doppler ◽  
Volume Index ◽  
Atrial Volume ◽  
Electromechanical Delay ◽  
Left Atrial Volume Index ◽  
Atrial Electromechanical Delay

Abstract Background: Tissue Doppler imaging (TDI)-derived atrial electromechanical delay (AEMD) has been reported to be useful for detecting paroxysmal atrial fibrillation (PAF). However, its usefulness remains unknown when analyzed along with patients seemingly at high-risk for AF as controls. From this standpoint, we investigated whether AEMD would be of use for identifying patients with PAF. Methods: We retrospectively analyzed TDI recordings to obtain AEMD in 63 PAF patients. Thirty-three patients with multiple cardiovascular risk factors (MRFs) but without history of AF and 50 healthy individuals served as disease and healthy controls, respectively. AEMD was defined as the time-interval between the electrocardiogram P-wave and the beginning of the spectral TDI-derived A’ for the septal (septal EMD) and lateral (lateral EMD) sides of the mitral annulus. Results: There was no significant difference in the left atrial volume index between PAF patients and disease controls (28 ± 9 mL/m 2 vs. 27 ± 5 mL/m 2 ). PAF patients had longer AEMD, particularly for the lateral EMD (75 ± 23 ms), compared with disease (62 ± 22 ms, P = 0.009) and healthy (54 ± 24 ms, P <0.001) controls. Multivariate logistic regression analysis revealed that the lateral EMD (OR 1.25, 95%CI 1.03 – 1.52, P = 0.023), along with the left atrial volume index (OR 2.25, 95%CI 1.44 – 3.51, P <0.001), was one of the significant independent associates of identifying PAF patients. Conclusions: This cross-sectional study indicates that even analyzed together with MRFs patients, AEMD remains useful for identifying patients at risk for AF. Our results need to be confirmed by a large-scale prospective study.

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