| Title |
Can an Offsite Expert Remotely Evaluate the Visual Estimation of Ejection Fraction via a Social Network Video Call?
|
|---|---|
| Published in |
Journal of Digital Imaging, May 2017
|
| DOI | 10.1007/s10278-017-9974-5 |
| Pubmed ID | |
| Authors |
Changsun Kim, Jin Hur, Bo Seung Kang, Hyuk Joong Choi, Jeong-Hun Shin, Tae-Hyung Kim, Jae Ho Chung |
| 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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 16% |
| Researcher | 6 | 14% |
| Student > Master | 6 | 14% |
| Other | 3 | 7% |
| Student > Postgraduate | 2 | 5% |
| Other | 5 | 11% |
| Unknown | 15 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 27% |
| Nursing and Health Professions | 8 | 18% |
| Psychology | 3 | 7% |
| Social Sciences | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 15 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 March 2018.
All research outputs
#1,881,329
of 22,971,207 outputs
Outputs from Journal of Digital Imaging
#40
of 1,058 outputs
Outputs of similar age
#38,258
of 310,587 outputs
Outputs of similar age from Journal of Digital Imaging
#2
of 22 outputs
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So far Altmetric has tracked 1,058 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 96% of its peers.
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We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.