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Methodist DeBakey Cardiovascular Journal 2023Heart and lung interaction within the thoracic cavity is well known during inhalation and exhalation, both spontaneously and during mechanical ventilation. Disease and... (Review)
Review
Heart and lung interaction within the thoracic cavity is well known during inhalation and exhalation, both spontaneously and during mechanical ventilation. Disease and dysfunction of one organ affect the function of the other. A review of the cause-and-effect relationship between cardiovascular disease and acute respiratory distress syndrome (ARDS) is of significance, as the disease burden of both conditions has both a national and global impact on health care. This literature review examines the relationship between cardiovascular disease and ARDS over the past 25 years.
Topics: Humans; Cardiovascular Diseases; Respiratory Distress Syndrome; Respiration, Artificial; Lung
PubMed: 37547902
DOI: 10.14797/mdcvj.1244 -
Frontiers in Cardiovascular Medicine 2023In cardiogenic shock various short-term mechanical assistances may be employed, including an Extra Corporeal Membrane Oxygenator and other non-dischargeable devices.... (Review)
Review
In cardiogenic shock various short-term mechanical assistances may be employed, including an Extra Corporeal Membrane Oxygenator and other non-dischargeable devices. Once hemodynamic stabilization is achieved and the patient evolves towards a persisting biventricular dysfunction or an underlying long-standing end-stage disease is present, aside from Orthotopic Heart Transplantation, a limited number of long-term therapeutic options may be offered. So far, only the Syncardia Total Artificial Heart and the Berlin Heart EXCOR (which is not approved for adult use in the United States unlike in Europe) are available for extensive implantation. In addition to this, the strategy providing two continuous-flow Left Ventricular Assist Devices is still off-label despite its widespread use. Nevertheless, every solution ensures at best a 70% survival rate (reflecting both the severity of the condition and the limits of mechanical support) with patients suffering from heavy complications and a poor quality of life. The aim of the present paper is to summarize the features, implantation techniques, and results of current devices used for adult Biventricular Mechanical Circulatory Support, as well as a glance to future options.
PubMed: 38028456
DOI: 10.3389/fcvm.2023.1234516 -
EuroIntervention : Journal of EuroPCR... Apr 2024
PubMed: 38629423
DOI: 10.4244/EIJ-E-24-00016 -
Journal of the American Society of... May 2024Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help... (Review)
Review
Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning can significantly improve fetal survival rates. Echocardiography is one of the most accessible and widely used diagnostic tools in the diagnosis of fetal congenital heart disease. However, traditional fetal echocardiography has limitations due to fetal, maternal, and ultrasound equipment factors and is highly dependent on the skill level of the operator. Artificial intelligence (AI) technology, with its rapid development utilizing advanced computer algorithms, has great potential to empower sonographers in time-saving and accurate diagnosis and to bridge the skill gap in different regions. In recent years, AI-assisted fetal echocardiography has been successfully applied to a wide range of ultrasound diagnoses. This review systematically reviews the applications of AI in the field of fetal echocardiography over the years in terms of image processing, biometrics, and disease diagnosis and provides an outlook for future research.
Topics: Humans; Artificial Intelligence; Pregnancy; Female; Ultrasonography, Prenatal; Echocardiography; Heart Defects, Congenital; Fetal Heart
PubMed: 38199332
DOI: 10.1016/j.echo.2023.12.013 -
Circulation Apr 2024A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform... (Review)
Review
A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.
Topics: United States; Humans; Artificial Intelligence; American Heart Association; Heart Diseases; Cardiovascular Diseases; Stroke
PubMed: 38415358
DOI: 10.1161/CIR.0000000000001201 -
Cureus Oct 2023Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article... (Review)
Review
Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.
PubMed: 37954711
DOI: 10.7759/cureus.46860 -
Enfermeria Intensiva Sep 2023End-stage heart failure (HF) is a condition whose only successful long-term treatment, with a survival of more than 10 years, is heart transplantation. However, limited... (Review)
Review
INTRODUCTION
End-stage heart failure (HF) is a condition whose only successful long-term treatment, with a survival of more than 10 years, is heart transplantation. However, limited organ availability and the progressive increase in the number of patients with advanced HF have served as an impetus for the development of implantable mechanical assistive devices.
AIM
To provide an overview of postoperative management and nursing care after the implementation of a Total Artificial Heart (TAH).
METHODS
A scoping review was carried out by consulting the PUBMED, CINAHL, and COCHRANE databases. From all the documents located, information was extracted on the date of publication, country of publication, type of study, and results of interest to answer the research question. In addition, the degree of recommendation was identified.
RESULTS
Twenty-three documents were included in the scoping review. Results were classified in relation to: 1) description of the CAT SynCardia®; 2) nursing care in the immediate postoperative period (management of the device and management of hematological, infectious, nephrological, nutritional complications, related to immobilization, sleep-rest disturbances, psychological disorders, and patient and family education); and 3) follow-up at home.
CONCLUSIONS
The complexity of implantation of the TAH, the multiple related complications that can arise during this process, both in the immediate post-operative and late, require a standardised and multidisciplinary management. The absence of standardised protocols raises the need for future studies to measure the effectiveness of care in patients with TAH. A multidisciplinary approach is crucial. Nurses must acquire autonomy and involvement in decision-making and develop competencies to address the patient's and family's physiological and psychosocial needs.
PubMed: 37743167
DOI: 10.1016/j.enfie.2023.08.006 -
The Journal of Heart and Lung... Sep 2023Reduced arterial pulsatility in continuous-flow left ventricular assist devices (CF-LVAD) patients has been implicated in clinical complications. Consequently, recent...
BACKGROUND
Reduced arterial pulsatility in continuous-flow left ventricular assist devices (CF-LVAD) patients has been implicated in clinical complications. Consequently, recent improvements in clinical outcomes have been attributed to the "artificial pulse" technology inherent to the HeartMate3 (HM3) LVAD. However, the effect of the "artificial pulse" on arterial flow, transmission of pulsatility into the microcirculation and its association with LVAD pump parameters is not known.
METHODS
The local flow oscillation (pulsatility index, PI) of common carotid arteries (CCAs), middle cerebral arteries (MCAs) and central retinal arteries (CRAs-representing the microcirculation) were quantified by 2D-aligned, angle-corrected Doppler ultrasound in 148 participants: healthy controls, n = 32; heart failure (HF), n = 43; HeartMate II (HMII), n = 32; HM3, n = 41.
RESULTS
In HM3 patients, 2D-Doppler PI in beats with "artificial pulse" and beats with "continuous-flow" was similar to that of HMII patients across the macro- and microcirculation. Additionally, peak systolic velocity did not differ between HM3 and HMII patients. Transmission of PI into the microcirculation was higher in both HM3 (during the beats with "artificial pulse") and in HMII patients compared with HF patients. LVAD pump speed was inversely associated with microvascular PI in HMII and HM3 (HMII, r = 0.51, p < 0.0001; HM3 "continuous-flow," r = 0.32, p = 0.0009; HM3 "artificial pulse," r = 0.23, p = 0.007), while LVAD pump PI was only associated with microcirculatory PI in HMII patients.
CONCLUSIONS
The "artificial pulse" of the HM3 is detectable in the macro- and microcirculation but without creating a significant alteration in PI compared with HMII patients. Increased transmission of pulsatility and the association between pump speed and PI in the microcirculation indicate that the future clinical care of HM3 patients may involve individualized pump settings according to the microcirculatory PI in specific end-organs.
Topics: Humans; Microcirculation; Heart-Assist Devices; Heart Failure; Heart Rate; Middle Cerebral Artery
PubMed: 37098374
DOI: 10.1016/j.healun.2023.04.002 -
Journal of Cardiovascular Development... Oct 2023The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and... (Review)
Review
The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and clinical comorbidities observed in epilepsy and arrhythmias. Neuro-cardiac electrophysiology mapping involves the comprehensive assessment of both neural and cardiac electrical activity, aiming to unravel the intricate connections and potential cross-talk between the brain and the heart. The emergence of artificial intelligence (AI) has revolutionized the field by enabling the analysis of large-scale data sets, complex signal processing, and predictive modeling. AI algorithms have been applied to neuroimaging, electroencephalography (EEG), electrocardiography (ECG), and other diagnostic modalities to identify subtle patterns, classify disease subtypes, predict outcomes, and guide personalized treatment strategies. In this review, we highlight the potential clinical implications of neuro-cardiac mapping and AI in the management of epilepsy and arrhythmias. We address the challenges and limitations associated with these approaches, including data quality, interpretability, and ethical considerations. Further research and collaboration between neurologists, cardiologists, and AI experts are needed to fully unlock the potential of this interdisciplinary field.
PubMed: 37887880
DOI: 10.3390/jcdd10100433 -
Scientific Reports Jul 2023Graph theory can be used to address problems with complex network structures. Congenital heart diseases (CHDs) involve complex abnormal connections between chambers,...
Graph theory can be used to address problems with complex network structures. Congenital heart diseases (CHDs) involve complex abnormal connections between chambers, vessels, and organs. We proposed a new method to represent CHDs based on graph theory, wherein vertices were defined as the spaces through which blood flows and edges were defined by the blood flow between the spaces and direction of the blood flow. The CHDs of tetralogy of Fallot (TOF) and transposition of the great arteries (TGA) were selected as examples for constructing directed graphs and binary adjacency matrices. Patients with totally repaired TOF, surgically corrected d-TGA, and Fontan circulation undergoing four-dimensional (4D) flow magnetic resonance imaging (MRI) were included as examples for constructing the weighted adjacency matrices. The directed graphs and binary adjacency matrices of the normal heart, extreme TOF undergoing a right modified Blalock-Taussig shunt, and d-TGA with a ventricular septal defect were constructed. The weighted adjacency matrix of totally repaired TOF was constructed using the peak velocities obtained from 4D flow MRI. The developed method is promising for representing CHDs and may be helpful in developing artificial intelligence and conducting future research on CHD.
Topics: Humans; Transposition of Great Vessels; Artificial Intelligence; Heart Defects, Congenital; Tetralogy of Fallot; Heart Septal Defects, Ventricular
PubMed: 37429950
DOI: 10.1038/s41598-023-38233-3