Chih-Yin Chien^1,2, Tsae-Jyy Wang¹, Pei-Hung Liao¹, Ying-Hsiang Lee^3,4,5,*, Wei-Sho Ho^6,7,*

Congenital Heart Disease, Vol.20, No.5, pp. 601-612, 2025, DOI:10.32604/chd.2025.072431 - 30 November 2025

Abstract Background: Cardiac implantable electronic devices (CIEDs) are essential for preventing sudden cardiac death in patients with cardiovascular diseases, but implantation procedures carry risks of complications such as infection, hematoma, and bleeding, with incidence rates of 3–4%. Previous studies have examined individual risk factors separately, but integrated predictive models are lacking. We compared the predictive performance and interpretability of artificial neural network (ANN) and logistic regression models to evaluate their respective strengths in clinical risk assessment. Methods: This retrospective study analyzed data from 180 patients who underwent cardiac implantable electronic device (CIED) implantation in Taiwan between 2017… More >

Shun Maki^1,*, Satoshi Nakano¹, Taiki Haga², Takehiro Niitsu¹, Ikuya Ueta¹

Congenital Heart Disease, Vol.20, No.5, pp. 547-558, 2025, DOI:10.32604/chd.2025.072277 - 30 November 2025

Abstract Background: Considering the limited evidence for acute postoperative nutritional therapy for congenital heart disease (CHD), this study evaluated the effects of achieving enteral nutrition (EN) targets in the acute postoperative phase on clinical outcomes in infants after congenital heart surgery. Methods: This retrospective cohort study, conducted in a multivalent pediatric intensive care unit (PICU), enrolled infants aged ≤6 months following congenital heart surgery between April 2021 and March 2023. Based on the American Society for Parenteral and Enteral Nutrition guidelines, the EN target was defined as two-thirds of the resting energy expenditure with a protein intake… More >

Khaled Elenizi¹, Abdullah Sharaf Aldeen², Nasser Alotaibi^3,*, Nagy Fagir², Hussien Hado², Mubarak Aldossari²

Congenital Heart Disease, Vol.20, No.5, pp. 539-546, 2025, DOI:10.32604/chd.2025.071226 - 30 November 2025

Abstract Persistent left superior vena cava (PLSVC) is a rare congenital anomaly that may complicate cardiac procedures when associated with a dilated coronary sinus (CS) and conduction disturbances. We report the case of a 27-year-old male with Wilson’s disease who presented with complete heart block. Echocardiography showed biatrial enlargement and severe CS dilation, while contrast-enhanced computed tomography (CT) confirmed PLSVC draining into the CS without a bridging vein. Anatomical constraints prevented cardiac resynchronization therapy, and dual-chamber pacemaker implantation proved technically challenging due to lead placement difficulties. This case highlights the importance of thorough preoperative assessment and More >

Zhuoxi Feng^#,1, Jinyang Liu^#,2, Zihao Wu¹, Ziran Geng¹, Zhimin Liu^1,*

Congenital Heart Disease, Vol.20, No.5, pp. 625-636, 2025, DOI:10.32604/chd.2025.069214 - 30 November 2025

Abstract Congenitally corrected transposition of the great arteries (CCTGA) is a rare congenital heart disease characterized by atrioventricular, ventriculoarterial, and conduction system discordance, commonly accompanied by atrioventricular block (AVB). Pacing in patients with CCTGA and AVB (both pediatric and adult) poses challenges in strategy selection, procedural complexity, and clinical decision-making due to limited evidence. Conventional morphological left ventricular pacing is widely adopted but may induce ventricular dyssynchrony, heart failure, and tricuspid valve dysfunction. While cardiac resynchronization therapy serves as an upgrade for pacing-induced cardiomyopathy and heart failure, its application may be limited by coronary sinus anatomical… More >

Gabriel Matheus Da Silva Batista, Lucas Pina Rodrigues, Andrey Jorge Serra^*

BIOCELL, Vol.49, No.10, pp. 1873-1885, 2025, DOI:10.32604/biocell.2025.067186 - 22 October 2025

Abstract Adipose-derived stem cells (ADSCs) therapy has emerged as a promising strategy for treating degenerative, inflammatory, and cardiometabolic diseases. In addition to their higher bioavailability in adipose tissue, ADSCs demonstrate superior activity in producing specific immune modulators and growth factors when compared to other stem cell types. The detrimental impact of heart failure (HF)—a condition that still lacks a fully effective therapy—has driven significant interest in the therapeutic potential of ADSCs. This interest is supported by robust evidence from experimental studies employing HF animal models. Accordingly, this review aims to explore the cardioprotective mechanisms through which More >

Xiaolin Cui¹, Khoon Lim^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.011173

Abstract 1 Introduction
Joint and cardiovascular diseases, such as osteoarthritis (OA) and myocardial infarction (MI), pose significant clinical challenges due to their limited regenerative capacity. The key to mitigating tissue damage and preventing the progression of OA and MI is to repair or even regenerate the infarcted tissue. At present, cell-based therapy is the primary strategy for tissue repair. Delivered cells could either differentiate into functional cells or secrete paracrine signals to promote onsite cell function. Both mechanisms have demonstrated potential in cartilage and cardiac tissue repair, both preclinically and clinically. In addition to cell therapy,… More >

Divya Arivalagan, Vignesh Ochathevan^*, Rubankumar Dhanasekaran

Congenital Heart Disease, Vol.20, No.4, pp. 477-501, 2025, DOI:10.32604/chd.2025.070372 - 18 September 2025

Abstract Background: The accurate identification of cardiac abnormalities is essential for proper diagnosis and effective treatment of cardiovascular diseases. Method: This work introduces an advanced methodology for detecting cardiac abnormalities and estimating electrocardiographic age (ECG Age) using sophisticated signal processing and deep learning techniques. This study looks at six main heart conditions found in 12-lead electrocardiogram (ECG) data. It addresses important issues like class imbalances, missing lead scenarios, and model generalizations. A modified residual neural network (ResNet) architecture was developed to enhance the detection of cardiac abnormalities. Results: The proposed ResNet demonst rated superior performance when compared with… More > Graphic Abstract

Jae Sung Son¹, Soo-Jin Kim^2,*

Congenital Heart Disease, Vol.20, No.4, pp. 421-440, 2025, DOI:10.32604/chd.2025.070250 - 18 September 2025

Abstract Background: Advancements in diagnostic tools, surgical techniques, and long-term management have significantly improved survival among individuals with congenital heart disease (CHD), leading to an evolving epidemiologic profile characterized by increasing procedural complexity and a growing adult CHD population. This study aimed to examine nationwide trends in CHD surgeries over a 17-year period, with a focus on temporal shifts in surgical volume, procedural complexity, and age-specific incidence. Methods: A total of 41,608 CHD surgeries and 85,417 surgical procedures performed between 2002 and 2018 were identified from a nationwide health insurance database. Temporal trends were evaluated using segmented… More >

Emrah Şişli^1,*, Pelin Köşger²

Congenital Heart Disease, Vol.20, No.4, pp. 531-537, 2025, DOI:10.32604/chd.2025.067271 - 18 September 2025

Abstract Residual atrioventricular valve regurgitation after correction of complete atrioventricular septal defect (cAVSD) is still not ideal. As a modification of the double-patch method, our technique comprises a suture-bite-wide strip of a third patch that is incorporated to the upper margin of the left side of the ventricular septal defect (VSD) patch. This third patch counteracts not only the valvular tissue loss caused by the suture bites but also the rightward displacement of the VSD patch in a bulged fashion that occurs with increased left ventricular pressure after weaning from cardiopulmonary bypass. This unfavorable outcome was More >

Deepak Mahto¹, Sudhakar Kumar¹, Sunil K. Singh¹, Amit Chhabra¹, Irfan Ahmad Khan², Varsha Arya^3,4, Wadee Alhalabi⁵, Brij B. Gupta^6,7,8,9,*, Bassma Saleh Alsulami¹⁰

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3743-3767, 2025, DOI:10.32604/cmes.2025.063427 - 30 June 2025

Abstract Cardiovascular diseases (CVDs) remain one of the foremost causes of death globally; hence, the need for several must-have, advanced automated diagnostic solutions towards early detection and intervention. Traditional auscultation of cardiovascular sounds is heavily reliant on clinical expertise and subject to high variability. To counter this limitation, this study proposes an AI-driven classification system for cardiovascular sounds whereby deep learning techniques are engaged to automate the detection of an abnormal heartbeat. We employ FastAI vision-learner-based convolutional neural networks (CNNs) that include ResNet, DenseNet, VGG, ConvNeXt, SqueezeNet, and AlexNet to classify heart sound recordings. Instead of… More >