TY  - BOOK
AU  - Fan, Kenneth L
TI  - Prevention, Diagnosis, and Management of Upper Extremity Lymphedema Complications: Altmetric Analysis of Online Media
SN  - 2169-7574
PY  - 2022///
KW  - IN PROCESS -- NOT YET INDEXED
KW  - MedStar Washington Hospital Center
KW  - Surgery/Plastic Surgery
KW  - Journal Article
N2  - Background: Traditional citation-based metrics do not capture the dissemination of upper extremity lymphedema (UEL) research that occurs online and in mainstream media. There is limited literature reporting the most impactful UEL articles based on citation rate and/or online mentions. We sought to use the Altmetric Attention Score (AAS) to determine the most impactful UEL articles in online media and to report trends in the diagnosis, treatment, and prevention of complications; Conclusions: Our findings suggest that alternative metrics measure distinct components of article impact and add an important dimension to understanding the overall impact of published research on UEL. Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons; Methods: The Altmetric database was queried to identify all published articles regarding the management, diagnosis, and prevention of complications seen in the setting of UEL. Extracted data points included article topic and type, journal, and number of online mentions on several platforms; Results: Our index search yielded 638 studies published between 2000 and 2021. Fifty articles with the highest AAS scores were included for analysis. The median AAS was 27.5, but the top four articles had AAS scores that were substantially higher (AAS >= 334) than all other studies. Of the top 50 articles, 68% (34/50) were original research. Of those, 23.5% (8/34) were randomized control trials. The most common article topic was the treatment of UEL (36%; 18/50) followed by diagnostic methods of UEL (30%; 15/50). There were a total of 1156 Twitter mentions (median:14) for the top 50 articles. Of all media platforms, news mentions correlated most strongly with AAS (R2 = 0.99, P < 0.001)
UR  - https://dx.doi.org/10.1097/GOX.0000000000004024
ER  -