Publications by authors named "Kpodonu J"

Rheumatic heart disease (RHD) is an important public health problem in Africa. Mapping the epidemiology of RHD involves elucidating its geographic distribution, temporal trends, and demographic characteristics. The prevalence of RHD in Africa varies widely, with estimates ranging from 2.

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To detect Hypertrophic Cardiomyopathy (HCM) from multiple views of Echocardiogram (cardiac ultrasound) videos. we propose , a novel framework that performs binary classification (HCM vs. no HCM) of echocardiogram videos directly using an ensemble of state-of-the-art deep VAR architectures models (SlowFast and I3D), and fuses their predictions using majority averaging ensembling.

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Over a decade of randomized controlled trial data demonstrate excellent outcomes with transcatheter aortic valve replacement or surgical aortic valve replacement for patients with symptomatic severe aortic stenosis regardless of surgical risk. The 2020 American College of Cardiology/American Heart Association guidelines recommend both options for low-risk AS patients aged 65 to 80 years. However, the fastest growing population of patients receiving transcatheter aortic valve replacement in the United States is <65 years old, with little data to support the practice.

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Background: Ejection fraction (EF) estimation informs patient plans in the ICU, and low EF can indicate ventricular systolic dysfunction, which increases the risk of adverse events including heart failure. Automated echocardiography models are an attractive solution for high-variance human EF estimation, and key to this goal are echocardiogram vector embeddings, which are a critical resource for computational researchers.

Objectives: The authors aimed to extract the vector embeddings from each echocardiogram in the EchoNet dataset using a classifier trained to classify EF as healthy (>50%) or unhealthy (<= 50%) to create an embeddings dataset for computational researchers.

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Background: Artificial intelligence (AI) has emerged as a tool to potentially increase the efficiency and efficacy of cardiovascular care and improve clinical outcomes. This study aims to provide an overview of applications of AI in cardiac surgery.

Methods: A systematic literature search on AI applications in cardiac surgery from inception to February 2024 was conducted.

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Article Synopsis
  • The document addresses corrections made to a previously published article identified by DOI: 10.5334/gh.1313.
  • It highlights specific errors or omissions that needed rectification to ensure accuracy and clarity in the research.
  • The corrections aim to enhance the reliability of the findings and conclusions presented in the original article.
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Article Synopsis
  • Rheumatic and congenital heart diseases, along with cardiomyopathies and hypertensive heart disease, lead to significant health issues and fatalities in low- and lower middle-income countries (LLMICs), impacting the poorest populations.
  • Access to advanced cardiac care is limited, primarily concentrated in urban areas, creating a gap in healthcare for rural communities due to shortages of diagnostics, medications, and trained personnel.
  • The Package of Essential NCD Interventions - Plus (PEN-Plus) aims to improve access to cardiac care in these regions by decentralizing services, and a coalition of global cardiac organizations is collaborating to implement effective strategies for managing severe cardiac diseases in high-poverty settings.
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Background: Acute type A aortic dissection (ATAAD) still challenges physicians and warrants emergent surgical management. Two main methods to reduce cerebrovascular events in ATAAD surgeries are antegrade cerebral perfusion (ACP) and retrograde cerebral perfusion (RCP). We conducted a systematic review and meta-analysis to compare the outcomes of ACP and RCP methods during the ATAAD surgery.

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Although entirely preventable, rheumatic heart disease (RHD), a disease of poverty and social disadvantage resulting in high morbidity and mortality, remains an ever-present burden in low-income and middle-income countries (LMICs) and rural, remote, marginalised and disenfranchised populations within high-income countries. In late 2021, the National Heart, Lung, and Blood Institute convened a workshop to explore the current state of science, to identify basic science and clinical research priorities to support RHD eradication efforts worldwide. This was done through the inclusion of multidisciplinary global experts, including cardiovascular and non-cardiovascular specialists as well as health policy and health economics experts, many of whom also represented or closely worked with patient-family organisations and local governments.

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Cardiac auscultation is an accessible diagnostic screening tool that can help to identify patients with heart murmurs, who may need follow-up diagnostic screening and treatment for abnormal cardiac function. However, experts are needed to interpret the heart sounds, limiting the accessibility of cardiac auscultation in resource-constrained environments. Therefore, the George B.

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Background: Global data on cardiac surgery centers are outdated and survey-based. In 1995, there were 0.7 centers per million population, ranging from one per 120,000 in North America to one per 33 million in sub-Saharan Africa.

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The global of paediatric and congenital heart disease (PCHD) is substantial. We propose a novel public health framework with recommendations for developing effective and safe PCHD services in low-income and middle-income countries (LMICs). This framework was created by the Global Initiative for Children's Surgery Cardiac Surgery working group in collaboration with a group of international rexperts in providing paediatric and congenital cardiac care to patients with CHD and rheumatic heart disease (RHD) in LMICs.

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This study compared the level of lubricity and pain reduction of a novel shea lubricant to 2% lidocaine gel during digital rectal examination (DRE). Our research group performed a 9-week single-blind non-inferiority trial at the Ho Teaching Hospital involving 153 patients. The primary outcome measure was the mean pain difference during the procedure using a Visual Analogue Scale.

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Background: Heart failure (HF) is recognized as a global public health disease associated with high morbidity and mortality. It is suggested that the main underlying causes of HF in developing countries differ from those identified in well-resourced countries. This study therefore presents the cardiovascular risk factors and the underlying aetiology of HF among admitted patients in a teaching Hospital in Ghana.

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Objectives: Machine learning (ML) has great potential, but there are few examples of its implementation improving outcomes. The thoracic surgeon must be aware of pertinent ML literature and how to evaluate this field for the safe translation to patient care. This scoping review provides an introduction to ML applications specific to the thoracic surgeon.

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Purpose: In low and middle-income countries, mechanical ventilators or commercially available devices used to offer continuous positive airway pressure are not readily affordable and available. In Ghana, nearly 10% of critically ill patients presenting to the emergency department require ventilator support.

Description: We designed, built, and tested a simple expiratory positive airway pressure (EPAP) device to provide adult respiratory support in low resource environments with or without supplemental oxygen and without the need for electricity.

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