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Can an Offsite Expert Remotely Evaluate the Visual Estimation of Ejection Fraction via a Social Network Video Call?

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Abstract

We aimed to investigate whether an offsite expert could effectively evaluate visually estimated ejection fraction (EF) while watching and guiding the echocardiographic procedure of an onsite novice practitioner using a social network video call. Sixty patients presenting to the intensive care unit and requiring echocardiography between October and November 2016 were included. Sixty novice sonographers without any previous experience of echocardiography participated. Prior to the procedure, the onsite cardiologist completed the echocardiography and determined the EF using the modified Simpson’s method (reference value). Then, the novice practitioner performed the echocardiography again with the offsite expert’s guidance via a social network video call. The EF was visually estimated by the offsite expert while watching the ultrasound video on the smartphone display. Spearman’s rank correlation and Bland-Altman plot analysis were conducted to assess the agreement between the two methods. There was excellent agreement between the two methods, with a correlation coefficient of 0.94 (p < 0.001). The Bland-Altman plot showed that the average bias was −3.05, and the limit of agreement (−10.3 to 4.2) was narrow. The offsite expert was able to perform an accurate visual estimation of ejection fraction remotely via a social network video call by mentoring the onsite novice sonographer.

ClinicalTrials.gov Identifier: NCT02960685.

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Correspondence to Bo Seung Kang.

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This study was approved by the Institutional Review Board of Hanyang university guri hospital.

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No external funding was secured for this study.

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The authors have no financial relationships relevant to this article to disclose.

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The authors declare that they have no conflicts of interest.

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Kim, C., Hur, J., Kang, B.S. et al. Can an Offsite Expert Remotely Evaluate the Visual Estimation of Ejection Fraction via a Social Network Video Call?. J Digit Imaging 30, 718–725 (2017). https://doi.org/10.1007/s10278-017-9974-5

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