Bunting KV, Steeds RP, Slater LT, Rogers JK, Gkoutos GV, Kotecha D.

Journal of the American Society of Echocardiography: Official publication of the American Society of Echocardiography (2019) doi.org/10.1016/j.echo.2019.08.015

Lay summary This multidisciplinary group provides a summary of different methods used to measure reproducibility in the context of echocardiography – a test that uses sound waves to produce live images of your heart. It is a summary of different statistical methods, with references to papers in the literature which have used these methods. The examples given in the paper (with graphs) are helpful for understanding the statistical concepts. The paper is predominantly meant as a guide for researchers on methodology, rather than for direct patient benefit. However, the authors provide an open access tool for researchers to make similar calculations for their own reproducibility, which is very helpful.

This lay summary was provided by Xiao Liu, member of HDR UK’s Early Career Researcher Committee

Abstract Echocardiography plays an essential role in the diagnosis and assessment of cardiovascular disease. Measurements derived from echocardiography are also used to determine the severity of disease, its progression over time, and to aid in the choice of optimal therapy. It is therefore clinically important that echocardiographic measurements be reproducible, repeatable, and reliable. There are a variety of statistical tests available to assess these parameters, and in this article the authors summarize those available for use by echocardiographers to improve their clinical practice. Correlation coefficients, linear regression, Bland-Altman plots, and the coefficient of variation are explored, along with their limitations. The authors also provide an online tool for the easy calculation of these statistics in the clinical environment (www.birmingham.ac.uk/echo). Quantifying and enhancing the reproducibility of echocardiography has important potential to improve the value of echocardiography as the basis for good clinical decision-making.