Trial reportBMJ open2022
Real-time automatic quantification of left ventricular function by hand-held ultrasound devices in patients with suspected heart failure: a feasibility study of a diagnostic test with data from general practitioners, nurses and cardiologists.
Trial report in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03547076 (The Use of Handheld Ultrasound Utilizing Support by Experts or Automatic Analyses for Improved Diagnostics at Remote Locations), which is not on this map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Use of Handheld Ultrasound Utilizing Support by Experts or Automatic Analyses for Improved Diagnostics at Remote Locations
Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Overcoming barriers in the use of artificial intelligence in point of care ultrasound.NPJ digital medicine · 2025Review
- Improvement initiatives in the diagnostic process of heart failure: a scoping review.Frontiers in cardiovascular medicine · 2025Review
- Assessment of an Artificial Intelligence Tool for Estimating Left Ventricular Ejection Fraction in Echocardiograms from Apical and Parasternal Long-Axis Views.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence-assisted evaluation of cardiac function by oncology staff in chemotherapy patients.European heart journal. Digital health · 2024Article
- Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases.European heart journal. Cardiovascular Imaging · 2024Article
- The importance of patient characteristics, operators, and image quality for the accuracy of heart failure diagnosis by general practitioners using handheld ultrasound devices.European heart journal. Imaging methods and practice · 2024Article
- Effect of implantable cardioverter defibrillator on primary prevention of sudden cardiac death in high-risk patients.American journal of translational research · 2023Article
- Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the feasibility and reliability of hand-held ultrasound (HUD) examinations with real-time automatic decision-making software for ejection fraction (autoEF) and mitral annular plane systolic excursion (autoMAPSE) by novices (general practitioners), intermediate users (registered cardiac nurses) and expert users (cardiologists), respectively, compared to reference echocardiography by cardiologists in an outpatient cohort with suspected heart failure (HF).
designFeasibility study of a diagnostic test. SETTING AND
participants166 patients with suspected HF underwent HUD examinations with autoEF and autoMAPSE measurements by five novices, three intermediate-skilled users and five experts. HUD results were compared with a reference echocardiography by experts. A blinded cardiologist scored all HUD recordings with automatic measurements as (1) discard, (2) accept, but adjust the measurement or (3) accept the measurement as it is. PRIMARY OUTCOME MEASURE: The feasibility of automatic decision-making software for quantification of left ventricular function.
resultsThe users were able to run autoEF and autoMAPSE in most patients. The feasibility for obtaining accepted images (score of ≥2) with automatic measurements ranged from 50% to 91%. The feasibility was lowest for novices and highest for experts for both autoEF and autoMAPSE (p≤0.001). Large coefficients of variation and wide coefficients of repeatability indicate moderate agreement. The corresponding intraclass correlations (ICC) were moderate to good (ICC 0.51-0.85) for intra-rater and poor (ICC 0.35-0.51) for inter-rater analyses. The findings of modest to poor agreement and reliability were not explained by the experience of the users alone.
conclusionNovices, intermediate and expert users were able to record four-chamber views for automatic assessment of autoEF and autoMAPSE using HUD devices. The modest feasibility, agreement and reliability suggest this should not be implemented into clinical practice without further refinement and clinical evaluation. TRIAL REGISTRATION NUMBER: NCT03547076.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.