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Diagnostic accuracy of telemedicine for detection of surgical site infection: a systematic review and meta-analysis

Lathan, Ross; Sidapra, Misha; Yiasemidou, Marina; Long, Judith; Totty, Joshua; Smith, George; Chetter, Ian

Authors

Ross Lathan

Misha Sidapra

Marina Yiasemidou

Judith Long

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Mr Josh Totty J.Totty@hull.ac.uk
NIHR Clinical Lecturer in Plastic Surgery

George Smith

Ian Chetter



Abstract

The Sars-CoV-2 pandemic catalysed integration of telemedicine worldwide. This systematic review assesses it’s accuracy for diagnosis of Surgical Site Infection (SSI). Databases were searched for telemedicine and wound infection studies. All types of studies were included, only paired designs were taken to meta-analysis. QUADAS-2 assessed methodological quality. 1400 titles and abstracts were screened, 61 full text reports were assessed for eligibility and 17 studies were included in meta-analysis, mean age was 47.1 ± 13.3 years. Summary sensitivity and specificity was 87.8% (95% CI, 68.4–96.1) and 96.8% (95% CI 93.5–98.4) respectively. The overall SSI rate was 5.6%. Photograph methods had lower sensitivity and specificity at 63.9% (95% CI 30.4–87.8) and 92.6% (95% CI, 89.9–94.5). Telemedicine is highly specific for SSI diagnosis is highly specific, giving rise to great potential for utilisation excluding SSI. Further work is needed to investigate feasibility telemedicine in the elderly population group.

Citation

Lathan, R., Sidapra, M., Yiasemidou, M., Long, J., Totty, J., Smith, G., & Chetter, I. (2022). Diagnostic accuracy of telemedicine for detection of surgical site infection: a systematic review and meta-analysis. npj Digital Medicine, 5(1), Article 108. https://doi.org/10.1038/s41746-022-00655-0

Journal Article Type Article
Acceptance Date Jul 4, 2022
Online Publication Date Aug 3, 2022
Publication Date 2022-12
Deposit Date Aug 3, 2022
Publicly Available Date Aug 4, 2022
Journal npj Digital Medicine
Print ISSN 2398-6352
Publisher Nature Research
Peer Reviewed Not Peer Reviewed
Volume 5
Issue 1
Article Number 108
DOI https://doi.org/10.1038/s41746-022-00655-0
Keywords Health Information Management; Health Informatics; Computer Science Applications; Medicine (miscellaneous)
Public URL https://hull-repository.worktribe.com/output/4044625

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http://creativecommons.org/licenses/by/4.0

Copyright Statement
© The Author(s) 2022.
Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.



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