Key result
AF and poor image quality reduce GP handheld ultrasound diagnostic accuracy for heart failure.
Why the study?
It was unknown whether patient characteristics, operators, and image quality could explain the accuracy of heart failure diagnosis by general practitioners using handheld ultrasound devices with automatic decision-support and telemedical support.
Do patient characteristics, operators, and image quality explain the accuracy of heart failure diagnosis by general practitioners using handheld ultrasound devices?
Observational (n=166)
Do patient characteristics, operators, and image quality explain the accuracy of heart failure diagnosis by general practitioners using handheld ultrasound devices?
Patient characteristics, operators, and image quality explain only a minor part of the modest accuracy of GP-performed heart failure diagnostics using handheld ultrasound devices, indicating a need for technological refinement.
AF and image factors explain little of modest GP handheld ultrasound accuracy for HF; hypothesis-generating for technological refinements.
Aims To evaluate whether the characteristics of patients, operators, and image quality could explain the accuracy of heart failure (HF) diagnostics by general practitioners (GPs) using handheld ultrasound devices (HUDs) with automatic decision-support software and telemedical support. Methods and results Patients referred to an outpatient cardiac clinic due to symptoms indicating HF were examined by one of five GPs after dedicated training. In total, 166 patients were included [median (inter-quartile range) age 73 (63–78) years; mean ± standard deviation ejection fraction 53 ± 10%]. The GPs considered whether the patients had HF in four diagnostic steps: (i) clinical examination, (ii) adding focused cardiac HUD examination, (iii) adding automatic decision-support software measuring mitral annular plane systolic excursion (autoMAPSE) and ejection fraction (autoEF), and (iv) adding telemedical support. Overall, the characteristics of patients, operators, and image quality explained little of the diagnostic accuracy. Except for atrial fibrillation [lower accuracy for HUD alone and after adding autoEF (P < 0.05)], no patient characteristics influenced the accuracy. Some differences between operators were found after adding autoMAPSE (P < 0.05). Acquisition errors of the four-chamber view and a poor visualization of the mitral plane were associated with reduced accuracy after telemedical support (P < 0.05). Conclusion The characteristics of patients, operators, and image quality explained just minor parts of the modest accuracy of GPs’ HF diagnostics using HUDs with and without decision-support software. Atrial fibrillation and not well-standardized recordings challenged the diagnostic accuracy. However, the accuracy was only modest in well-recorded images, indicating a need for refinement of the technology.
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Magelssen et al. (2023) conducted an observational in Heart failure (n=166). Handheld ultrasound devices (HUDs) with automatic decision-support software and telemedical support was evaluated on Accuracy of heart failure diagnostics. Atrial fibrillation and poor image quality significantly reduced the diagnostic accuracy of GPs using handheld ultrasound devices for heart failure (P < 0.05), though overall accuracy remained modest.
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