Adil Hussain^1,*, Ayesha Aslam²

Journal on Artificial Intelligence, Vol.6, pp. 129-152, 2024, DOI:10.32604/jai.2024.050277

Abstract The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly. The utilization of machine learning in the medical domain has witnessed a notable surge due to its ability to discern patterns from vast amounts of data. Machine learning algorithms that can categorize cases of cardiovascular illness may help doctors reduce the number of wrong diagnoses. This research investigates the efficacy of different machine learning algorithms in predicting cardiovascular disease in accordance with risk factors. This study utilizes a variety of machine learning models, More >

Shuliang Xia^1,2,3,#, Huikang Tao^2,#, Shixin Su⁴, Xinxin Chen², Li Ma², Jianru Li⁵, Bei Gao⁶, Xumei Liu⁵, Lei Pi⁷, Jinqing Feng⁴, Fengxiang Li², Jia Li^4,*, Zhiwei Zhang^1,3,*

Congenital Heart Disease, Vol.19, No.2, pp. 247-256, 2024, DOI:10.32604/chd.2024.052583

Abstract Aims: Multiple genes and environmental factors are known to be involved in congenital heart disease (CHD), but epigenetic variation has received little attention. Monozygotic (MZ) twins with CHD provide a unique model for exploring this phenomenon. In order to investigate the potential role of Deoxyribonucleic Acid (DNA) methylation in CHD pathogenesis, the present study examined DNA methylation variation in MZ twins discordant for CHD, especially ventricular septal defect (VSD). Methods and Results: Using genome-wide DNA methylation profiles, we identified 4004 differentially methylated regions (DMRs) in 18 MZ twin pairs discordant for CHD, and 2826 genes were… More > Graphic Abstract

Dominique Vervoort^1,2,3,*, Amy Verstappen³, Sreehari Madhavankutty Nair⁴, Chong Chin Eu⁵, Bistra Zheleva^3,6

Congenital Heart Disease, Vol.19, No.2, pp. 131-138, 2024, DOI:10.32604/chd.2024.049814

Abstract This article has no abstract. More >

Camden L. Hebson^1,*, Kyle Bliton², Amr Y. Hammouda¹, Kaitlyn Barr³, W. Hampton Gray⁴, Mohini Gunnett², Waldemar F. Carlo¹

Congenital Heart Disease, Vol.19, No.2, pp. 185-195, 2024, DOI:10.32604/chd.2024.048871

Abstract D-transposition of the great arteries (d-TGA) is surgically repaired with the arterial switch operation (ASO) with excellent results, however short and long-term morbidities still develop including neurocognitive delay. Clinically significant central sleep apnea is uncommon in non-premature infants, but when present indicates immature autonomic control of respiration likely due to a neurologic disorder. We report the unanticipated finding of central sleep apnea in four-term neonates with d-TGA after uncomplicated ASO, with the short-term complication of delayed hospital discharge and long-term concerns regarding this early marker of brain immaturity and its hindrance to normal development. Within More >

Yang Wang^#, Xun Yang^#, Mingtang Ye, Yuhang Zhao, Runsen Chen, Min Da, Zhiqi Wang, Xuming Mo, Jirong Qi^*

Congenital Heart Disease, Vol.19, No.2, pp. 219-231, 2024, DOI:10.32604/chd.2024.048314

Abstract Congenital heart disease (CHD), the most prevalent congenital ailment, has seen advancements in the “dual indicator” screening program. This facilitates the early-stage diagnosis and treatment of children with CHD, subsequently enhancing their survival rates. While cardiac auscultation offers an objective reflection of cardiac abnormalities and function, its evaluation is significantly influenced by personal experience and external factors, rendering it susceptible to misdiagnosis and omission. In recent years, continuous progress in artificial intelligence (AI) has enabled the digital acquisition, storage, and analysis of heart sound signals, paving the way for intelligent CHD auscultation-assisted diagnostic technology. Although More > Graphic Abstract

Hina Naz¹, Zuping Zhang^1,*, Mohammed Al-Habib¹, Fuad A. Awwad², Emad A. A. Ismail², Zaid Ali Khan³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2673-2696, 2024, DOI:10.32604/cmc.2024.049186

Abstract Cardiovascular disease is the leading cause of death globally. This disease causes loss of heart muscles and is also responsible for the death of heart cells, sometimes damaging their functionality. A person’s life may depend on receiving timely assistance as soon as possible. Thus, minimizing the death ratio can be achieved by early detection of heart attack (HA) symptoms. In the United States alone, an estimated 610,000 people die from heart attacks each year, accounting for one in every four fatalities. However, by identifying and reporting heart attack symptoms early on, it is possible to… More >

Fatma Nese Efil¹, Sania Qureshi^1,2,3, Nezihal Gokbulut^1,4, Kamyar Hosseini^1,3, Evren Hincal^1,4,*, Amanullah Soomro²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 485-512, 2024, DOI:10.32604/cmes.2024.047907

Abstract The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in… More >

Sipawath Khamplod^1,2, Yodying Kaolawanich^1,2, Khemajira Karaketklang³, Nithima Ratanasit^1,2,*

Congenital Heart Disease, Vol.19, No.1, pp. 93-105, 2024, DOI:10.32604/chd.2024.048631

Abstract Background: Atrial septal defect (ASD) is a common form of adult congenital heart disease that can lead to long-term adverse outcomes if left untreated. Early closure of ASD has been associated with excellent outcomes and lower complication rates. However, there is limited evidence regarding the prognosis of ASD closure in older adults. This study aims to evaluate the mortality rates in older ASD patients with and without closure. Methods: A retrospective cohort study was conducted on patients aged 40 years or older with ASD between 2001 and 2017. Patients were followed up to assess all-cause… More > Graphic Abstract

Fu Guan^1,*, Matthias Gass², Florian Berger², Heiko Schneider¹, Firat Duru^1,3, Thomas Wolber^1,3,*

Congenital Heart Disease, Vol.19, No.1, pp. 85-92, 2024, DOI:10.32604/chd.2024.047266

Abstract Aims: Although the application of ultrasound-guided vascular puncture and Z-stitch hemostasis to manage femoral access has been widely utilized, there is limited data on this combined application in adult congenital heart disease (ACHD) patients undergoing electrophysiological (EP) procedures. We sought to evaluate the safety and efficacy of ultrasound-guided puncture and postprocedural Z-stitch hemostasis for ACHD patients undergoing EP procedures. Methods and Results: The population of ACHD patients undergoing transfemoral EP procedures at the University of Zurich Heart Center between January 2019 and December 2022 was observed and analyzed. During the study period, femoral access (left/right, arterial/venous)… More >

Albert Osom¹, Krysta S. Barton², Katie Sexton^3,4, Lyndia Brumback¹, Joyce P. Yi-Frazier⁴, Abby R. Rosenberg^5,6, Ruth Engelberg⁷, Jill M. Steiner^8,*

Congenital Heart Disease, Vol.19, No.1, pp. 33-48, 2024, DOI:10.32604/chd.2024.046656

Abstract Social determinants of health (SDOH) affect quality of life. We investigated SDOH impacts on self-perceived resilience among people with adult congenital heart disease (ACHD). Secondary analysis of data from two complementary studies: a survey study conducted May 2021–June 2022 and a qualitative study conducted June 2020–August 2021. Resilience was assessed through CD-RISC10 score (range 0–40, higher scores reflect greater self-perceived resilience) and interview responses. Sociodemographic and SDOH (education, employment, living situation, monetary stability, financial dependency, area deprivation index) data were collected by healthcare record review and self-report. We used linear regression with robust standard errors… More > Graphic Abstract