Abstract:Atrial fibrillation (AF) is a common cardiac arrhythmia in the general population (Kjerpeseth et al., 2021) and is associated with increased cardiovascular morbidity and mortality. (Tanaka et al., 2021) Early recognition of AF could allow for more successful control of arrhythmia and protect the patient from adverse consequences. (Hindricks et al., 2021) Therefore, it is crucial to identify patients who are at an increased risk of developing AF. Complete right bundle branch block (CRBBB) is one of the most fre… Show more
“…Several studies have examined risk factors for AF, which could be found using ECG. Interatrial, first-degree atrioventricular (AV), and right bundle branch blocks are reportedly risk factors for the incidence of AF [38][39][40] . ECG measurements and findings, such as PAC, p wave, and LVH, are reportedly risk factors for the incidence of AF 41 .…”
Atrial fibrillation (AF) is an arrhythmic disease. Prediction of AF development in healthy individuals is important before serious complications occur. We aimed to develop a risk prediction score for future AF using participants’ data, including electrocardiogram (ECG) measurements and information such as age and sex. We included 88,907 Japanese participants, aged 30–69 years, who were randomly assigned to derivation and validation cohorts in a ratio of 1:1. We performed multivariate logistic regression analysis and obtained the standardised beta coefficient of relevant factors and assigned scores to them. We created a score based on prognostic factors for AF to predict its occurrence after five years and applied it to validation cohorts to assess its reproducibility. The risk score ranged from 0 to 17, consisting of age, sex, PR prolongation, QT corrected for heart rate prolongation, left ventricular hypertrophy, premature atrial contraction, and left axis deviation. The area under the curve was 0.75 for the derivation cohort and 0.73 for the validation cohort. The incidence of new-onset AF reached over 2% at 10 points of the risk score in both cohorts. Thus, in this study, we showed the possibility of predicting new-onset AF using ECG findings and simple information.
“…Several studies have examined risk factors for AF, which could be found using ECG. Interatrial, first-degree atrioventricular (AV), and right bundle branch blocks are reportedly risk factors for the incidence of AF [38][39][40] . ECG measurements and findings, such as PAC, p wave, and LVH, are reportedly risk factors for the incidence of AF 41 .…”
Atrial fibrillation (AF) is an arrhythmic disease. Prediction of AF development in healthy individuals is important before serious complications occur. We aimed to develop a risk prediction score for future AF using participants’ data, including electrocardiogram (ECG) measurements and information such as age and sex. We included 88,907 Japanese participants, aged 30–69 years, who were randomly assigned to derivation and validation cohorts in a ratio of 1:1. We performed multivariate logistic regression analysis and obtained the standardised beta coefficient of relevant factors and assigned scores to them. We created a score based on prognostic factors for AF to predict its occurrence after five years and applied it to validation cohorts to assess its reproducibility. The risk score ranged from 0 to 17, consisting of age, sex, PR prolongation, QT corrected for heart rate prolongation, left ventricular hypertrophy, premature atrial contraction, and left axis deviation. The area under the curve was 0.75 for the derivation cohort and 0.73 for the validation cohort. The incidence of new-onset AF reached over 2% at 10 points of the risk score in both cohorts. Thus, in this study, we showed the possibility of predicting new-onset AF using ECG findings and simple information.
Atrial fibrillation (AF) is a common cardiac arrhythmia in the general population (Kjerpeseth et al., 2021) and is associated with increased cardiovascular morbidity and mortality. (Tanaka et al., 2021) Early recognition of AF could allow for more successful control of arrhythmia and protect the patient from adverse consequences. (Hindricks et al., 2021) Therefore, it is crucial to identify patients who are at an increased risk of developing AF. Complete right bundle branch block (CRBBB) is one of the most frequent alterations observed on
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