Predictors of atrial tachyarrhythmias in adults with congenital heart disease

Cambronero-Cortinas, Esther; Moratalla-Haro, Pedro; González–García, Ana; Ávila, Pablo; Papachristidis, Alexandros; Bret-Zurita, Montserrat; Ruiz‐Cantador, Jose; Rivero-Jiménez, Natalia; Peinado, Rafaél; Oliver, José M.

doi:10.33963/kp.15644

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…On the other hand, in our study, the percentage of diabetic patients was higher than in the geriatric CHD population in Quebec/Canada (16%) and South Alberta (13%) [6,7]. As diabetes is a risk factor for arrhythmias in ACHD [18] and it was identified as an independent predictor of all-cause mortality [6], its occurrence among ACHD survivors in Poland deserves special attention.…”

Section: Discussionmentioning

confidence: 75%

The burden of cardiovascular risk factors among seniors with congenital heart disease: A single tertiary center experience

et al. 2021

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Background:The number of adults with congenital heart disease (ACHD) surviving to old age is increasing worldwide. Acquired cardiovascular comorbidities may complicate the course and treatment of the underlying congenital disease and worsen the prognosis. Aims:The study aimed to assess the burden of cardiovascular (CV) risk factors among elderly patients with ACHD. Methods:A retrospective analysis of data on all patients ≥60 years of age hospitalized in a tertiary clinic for ACHD was performed from July 2013 to March 2020. We collected information on smoking status, body mass index, and the presence of dyslipidemia, systemic hypertension, and diabetes. Results:The most common CV risk factors among 322 patients ≥60 years of age (median age 66 years; 34% men) were: being overweight/obesity (65.5%), dyslipidemia (64.9%), and arterial hypertension (60.6%). Over 21% of patients suffered from diabetes, and 25.8% were smokers. Over 54% of patients had two or 3 CV risk factors. Patients above 70 years of age were healthier in terms of being overweight/obesity, dyslipidemia, and smoking status. Patients with mild ACHD were more likely hypertensive compared to individuals with complex defects. The highest CV burden was noted in younger men with mild ACHD. Conclusions:We demonstrated a high burden of CV risk factors in seniors with ACHD. Special attention should be paid to the identification and control of classical CV risk factors in order to prevent acquired CV disease in this population.

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Section: Discussionmentioning

confidence: 75%

The burden of cardiovascular risk factors among seniors with congenital heart disease: A single tertiary center experience

et al. 2021

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“…Traditional diagnosis of TOF is after a baby is born, often after the infant had an episode of cyanosis during crying or feeding. The most common test is an echocardiogram [4], an ultrasound of the heart that can show problems with the heart structure and how well the heart is working with this defect. Recently, computed tomography (CT) has shown its success in the differential diagnosis of TOF [5], since it can provide detailed images of many types of cardiovascular issue; besides, computed tomography (CT) can be performed even if the subject has an implanted medical device, unlike magnetic resonance imaging (MRI) [6].…”

Section: Introductionmentioning

confidence: 99%

SOSPCNN: Structurally Optimized Stochastic Pooling Convolutional Neural Network for Tetralogy of Fallot Recognition

Wang

Chu³

et al. 2021

Wireless Communications and Mobile Computing

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Aim. This study proposes a new artificial intelligence model based on cardiovascular computed tomography for more efficient and precise recognition of Tetralogy of Fallot (TOF). Methods. Our model is a structurally optimized stochastic pooling convolutional neural network (SOSPCNN), which combines stochastic pooling, structural optimization, and convolutional neural network. In addition, multiple-way data augmentation is used to overcome overfitting. Grad-CAM is employed to provide explainability to the proposed SOSPCNN model. Meanwhile, both desktop and web apps are developed based on this SOSPCNN model. Results. The results on ten runs of 10-fold crossvalidation show that our SOSPCNN model yields a sensitivity of 92.25 ± 2.19 , a specificity of 92.75 ± 2.49 , a precision of 92.79 ± 2.29 , an accuracy of 92.50 ± 1.18 , an F1 score of 92.48 ± 1.17 , an MCC of 85.06 ± 2.38 , an FMI of 92.50 ± 1.17 , and an AUC of 0.9587. Conclusion. The SOSPCNN method performed better than three state-of-the-art TOF recognition approaches.

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Predictors of atrial tachyarrhythmias in adults with congenital heart disease

Cited by 2 publications

References 26 publications

The burden of cardiovascular risk factors among seniors with congenital heart disease: A single tertiary center experience

The burden of cardiovascular risk factors among seniors with congenital heart disease: A single tertiary center experience

SOSPCNN: Structurally Optimized Stochastic Pooling Convolutional Neural Network for Tetralogy of Fallot Recognition

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