scholarly journals Brugada Syndrome With Ventricular Tachycardia and Fibrillation Related to Hypokalemia

2003 ◽  
Vol 67 (1) ◽  
pp. 93-95 ◽  
Author(s):  
Tsutomu Araki ◽  
Tetsuo Konno ◽  
Hideki Itoh ◽  
Hidekazu Ino ◽  
Masami Shimizu
Keyword(s):  
Ventricular Tachycardia ◽  
Brugada Syndrome ◽  
Ventricular Tachycardia And Fibrillation

scholarly journals ACQUIRED BRUGADA SYNDROME PRESENTING AS VENTRICULAR TACHYCARDIA STORM

CHEST Journal ◽  
2007 ◽  
Vol 132 (4) ◽  
pp. 716A ◽  
Author(s):  
Jacob S. Koruth ◽  
Sunil Jagadesh ◽  
Karen S. Rovang ◽  
Aryan N. Mooss ◽  
Tom Hee ◽  
...  
Keyword(s):  
Ventricular Tachycardia ◽  
Brugada Syndrome

Brugada syndrome unmasked by left ventricle posteromedial papillary muscle ventricular tachycardia: Coincidence or consequence

2021 ◽  
Author(s):  
Javier Pinos ◽  
Tiago Luiz Luz Leiria ◽  
Bernardo Boccalon ◽  
Marcelo Lapa Kruse ◽  
Gustavo Glotz De Lima
Keyword(s):  
Ventricular Tachycardia ◽  
Left Ventricle ◽  
Papillary Muscle ◽  
Brugada Syndrome

scholarly journals Incorporating Latent Variables Using Nonnegative Matrix Factorization Improves Risk Stratification in Brugada Syndrome

2020 ◽  
Vol 9 (22) ◽  
Author(s):  
Gary Tse ◽  
Jiandong Zhou ◽  
Sharen Lee ◽  
Tong Liu ◽  
George Bazoukis ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ventricular Tachycardia ◽  
Ventricular Fibrillation ◽  
Risk Stratification ◽  
Matrix Factorization ◽  
Brugada Syndrome ◽  
Latent Variables ◽  
Odds Ratio ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix

Background A combination of clinical and electrocardiographic risk factors is used for risk stratification in Brugada syndrome. In this study, we tested the hypothesis that the incorporation of latent variables between variables using nonnegative matrix factorization can improve risk stratification compared with logistic regression. Methods and Results This was a retrospective cohort study of patients presented with Brugada electrocardiographic patterns between 2000 and 2016 from Hong Kong, China. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation. The external validation cohort included patients from 3 countries. A total of 149 patients with Brugada syndrome (84% males, median age of presentation 50 [38–61] years) were included. Compared with the nonarrhythmic group (n=117, 79%), the spontaneous ventricular tachycardia/ ventricular fibrillation group (n=32, 21%) were more likely to suffer from syncope (69% versus 37%, P =0.001) and atrial fibrillation (16% versus 4%, P =0.023) as well as displayed longer QTc intervals (424 [399–449] versus 408 [386–425]; P =0.020). No difference in QRS interval was observed (108 [98–114] versus 102 [95–110], P =0.104). Logistic regression found that syncope (odds ratio, 3.79; 95% CI, 1.64–8.74; P =0.002), atrial fibrillation (odds ratio, 4.15; 95% CI, 1.12–15.36; P =0.033), QRS duration (odds ratio, 1.03; 95% CI, 1.002–1.06; P =0.037) and QTc interval (odds ratio, 1.02; 95% CI, 1.01–1.03; P =0.009) were significant predictors of spontaneous ventricular tachycardia/ventricular fibrillation. Increasing the number of latent variables of these electrocardiographic indices incorporated from n=0 (logistic regression) to n=6 by nonnegative matrix factorization improved the area under the curve of the receiving operating characteristics curve from 0.71 to 0.80. The model improves area under the curve of external validation cohort (n=227) from 0.64 to 0.71. Conclusions Nonnegative matrix factorization improves the predictive performance of arrhythmic outcomes by extracting latent features between different variables.

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