ArticleHypertension research : official journal of the Japanese Society of Hypertension2024
Implementing focused echocardiography and AI-supported analysis in a population-based survey in Lesotho: implications for community-based cardiovascular disease care models.
Article in Hypertension research : official journal of the Japanese Society of Hypertension, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- ECG Criteria for Left Ventricular Hypertrophy in Hypertensive Black Africans: Insights from the coArtHA Trial.Global heart · 2026Trial
- Artificial Intelligence (AI) in Home-Care and Community Nursing: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Decentralized community-based hub-intermediary-spoke model for rapid cardiac ultrasound triage for early heart failure detection: findings from the Heart2Miss initiative.European heart journal. Digital health · 2026Article
- A perspective on AI implementation in medical imaging in LMICs: challenges, priorities, and strategies.European radiology · 2026Article
- From Echocardiography to CT/MRI: Lessons for AI Implementation in Cardiovascular Imaging in LMICs-A Systematic Review and Narrative Synthesis.Bioengineering (Basel, Switzerland) · 2025Review
- AI assisted focused cardiac ultrasound in preventive cardiology - a perspective.NPJ cardiovascular health · 2025Review
- Machine learning in the prevention of heart failure.Heart failure reviews · 2025Review
- Artificial intelligence-enhanced patient evaluation: bridging art and science.European heart journal · 2024Review
- Artificial Intelligence-Based Left Ventricular Ejection Fraction by Medical Students for Mortality and Readmission Prediction.Diagnostics (Basel, Switzerland) · 2024Article
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Authors and funding
12 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In settings where access to expert echocardiography is limited, focused echocardiography, combined with artificial intelligence (AI)-supported analysis, may improve diagnosis and monitoring of left ventricular hypertrophy (LVH). Sixteen nurses/nurse-assistants without prior experience in echocardiography underwent a 2-day hands-on intensive training to learn how to assess parasternal long axis views (PLAX) using an inexpensive hand-held ultrasound device in Lesotho, Southern Africa. Loops were stored on a cloud-drive, analyzed using deep learning algorithms at the University Hospital Basel, and afterwards confirmed by a board-certified cardiologist. The nurses/nurse-assistants obtained 756 echocardiograms. Of the 754 uploaded image files, 628 (83.3%) were evaluable by deep learning algorithms. Of those, results of 514/628 (81.9%) were confirmed by a cardiologist. Of the 126 not evaluable by the AI algorithm, 46 (36.5%) were manually evaluable. Overall, 660 (87.5%) uploaded files were evaluable and confirmed. Following short-term training of nursing cadres, a high proportion of obtained PLAX was evaluable using AI-supported analysis. This could be a basis for AI- and telemedical support in hard-to-reach areas with minimal resources.
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