Difference in the prevalence of intracardiac thrombus on the first presentation of atrial fibrillation versus flutter in the pediatric and congenital heart disease population

2020 ◽  
Vol 31 (12) ◽  
pp. 3243-3250
Author(s):  
Omar Meziab ◽  
Luciana Marcondes ◽  
Kevin G. Friedman ◽  
Edward T. O'Leary ◽  
Michelle Gurvitz ◽  
...  
Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Ngoc Thanh Kim ◽  
Thanh Tung Le ◽  
Doan Loi Do ◽  
Thanh Huong Truong

Introduction: In Vietnam, knowledge about renal function in adults with congenital heart disease (CHD) is limited. Hypothesis: This study aims to estimate incidence of renal dysfunction in adults with congenital heart disease and risk factors. Methods: This is a cross-sectional study, including 365 CHD patients more than 16 years old. We collected clinical and para-clinical information, estimated glomerular filtration rate (GFR) and calculated the odds ratio (OR) for reduced GFR. Results: Totally, 52.8% patients had GFR < 90 ml/phút/1.73 m 2 . Logistic regression had confirmed the OR for GFR < 90 ml/phút/1.73 m 2 in the group > 60-years-old, the group with atrial fibrillation, the group with heart failure (based on NT-proBNP > 125 pmol/L), and the group with pulmonary arterial hypertension (based on pulmonary artery systolic pressure > 50 mmHg by echocardiography) were 6.46 (95% CI: 1.37 - 30.41), 7.58 (95% CI: 1.66 - 34.56), 2.98 (95% CI: 1.49 - 5.98) and 1.84 (95% CI: 1.02 - 3.33), respectively. Conclusions: Renal dysfunction is common in adults with CHD. Age > 60 years-old, atrial fibrillation, heart failure, and pulmonary arterial hypertension were risk factors for renal dysfunction in adults with CHD.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A.J Fischer ◽  
D Enders ◽  
H Baumgartner ◽  
G.P Diller

Abstract Background Arrhythmias are a major contributor to morbidity and mortality in adult patients with congenital heart disease (ACHD). Advances in ablation technology have contributed to improved management and reduction of symptoms in this population. However, only limited data exist on the use and outcome of these technologies in large community-based cohorts of ACHD patients and on the impact of specialized centres on recurrence of arrhythmias. Purpose We performed a retrospective analysis based on data from one of the largest German Health Insurance Companies (approx. 9 million insured members), acquiring real-world data on frequency of invasive electrophysiological studies (EPS) in Germany between 2005 and 2018. ACHD patients were identified based on ICD codes and the spectrum of disease as well as the impact of EPS being performed at specialized ACHD centres was analysed. Results Out of 45,761 eligible ACHD patients in the database, we identified 2,433 EPS performed in 1,706 ACHD (51% female, median age 55.4 years, complexity of CHD mild, moderate and severe in 50.6%, 33.2%,16.2%, respectively). Over the study period the annual number of EPS increased by 207%. The majority of procedures were for supraventricular tachycardias (85.9%). Of these procedures atrial fibrillation accounted for 35.1%, atrial flutter for 29.4% and other supraventricular tachycardias/pre-excitation syndromes for 29.9% of cases. The majority of EPS (64.3%) was performed at non-specialized centres including 40.2% of cases in patients with complex disease. Overall, the re- intervention rate within 12 months of the primary EPS was 14.5%. Whereas in ACHD patients with simple and moderate complexity disease no obvious difference in 12-months re- intervention rate was observed between specialized and non-specialised centres (15.5% vs. 15.0%), in patients with complex disease the reintervention rate was 41.6% higher for non-specialized centres (13.6% vs. 9.6%). Conclusion Our large real- world analysis shows an increasing need for invasive electrophysiological studies in ACHD patients. The vast majority of procedures was performed for supraventricular arrhythmias including in atrial fibrillation and flutter ablation. Re-interventions were frequently required in this unique and anatomically challenging population. Alarmingly, many procedures were performed at non-specialized centres, although current guidelines recommend that interventions in complex patients should remain reserved for experienced high-volume centres. Funding Acknowledgement Type of funding source: None


2019 ◽  
Vol 287 ◽  
pp. 148-154 ◽  
Author(s):  
Victor Waldmann ◽  
Mikael Laredo ◽  
Sylvia Abadir ◽  
Blandine Mondésert ◽  
Paul Khairy

2014 ◽  
Vol 30 (10) ◽  
pp. S193
Author(s):  
D. Wan ◽  
J. Grewal ◽  
A. Krahn ◽  
J Yeung- Lai-Wah ◽  
M. Kiess ◽  
...  

Author(s):  
Kok Wai Giang ◽  
Saga Helgadottir ◽  
Mikael Dellborg ◽  
Giovanni Volpe ◽  
Zacharias Mandalenakis

Abstract Aims To improve short-and long-term predictions of mortality and atrial fibrillation among patients with congenital heart disease from a nationwide population using neural networks. Methods and results The Swedish National Patient Register and the Cause of Death Register were used to identify all patients with congenital heart disease born from 1970 to 2017. A total of 71,941 congenital heart disease patients were identified and followed-up from birth until the event or end of study in 2017. Based on data from a nationwide population, a neural network model was obtained to predict mortality and atrial fibrillation. Logistic regression based on the same data was used as a baseline comparison. Of 71,941 congenital heart disease patients, a total of 5768 died (8.02%) and 995 (1.38%) developed atrial fibrillation over time with a mean follow-up time of 16.47 years (standard deviation 12.73 years). The performance of neural network models in predicting the mortality and atrial fibrillation was higher than the performance of logistic regression regardless of the complexity of the disease, with an average Area Under the Receiver Operating Characteristic of &gt; 0.80 and &gt;0.70, respectively. The largest differences were observed in mortality and complexity of congenital heart disease over time. Conclusion We found that neural networks can be used to predict mortality and atrial fibrillation on a nationwide scale using data that are easily obtainable by clinicians. In addition, neural networks showed a high performance overall and, in most cases, with better performance for prediction as compared with more traditional regression methods.


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