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The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries

BACKGROUND: Surveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults. METHODS: The training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal...

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Autores principales: Shitrit, Pnina, Chowers, Michal Y., Muhsen, Khitam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909272/
https://www.ncbi.nlm.nih.gov/pubmed/36778736
http://dx.doi.org/10.3389/fmed.2023.1023385
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author Shitrit, Pnina
Chowers, Michal Y.
Muhsen, Khitam
author_facet Shitrit, Pnina
Chowers, Michal Y.
Muhsen, Khitam
author_sort Shitrit, Pnina
collection PubMed
description BACKGROUND: Surveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults. METHODS: The training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal hysterectomies (N = 523) during 2015–2018. The gold standard for the validation of the screening tool was the presence of SSI as determined by a trained infection control practitioner, via manual full medical record review, using the US Center for Disease Control and Prevention criteria. Using multivariable regression models, we identified the correlates of SSI. Patients who had at least one of these correlates were classified as likely to having SSI and those who did not have any of the correlates were classified as unlikely to have SSI. We calculated the sensitivity and specificity of this tool compared to the gold standard and applied the tool to a validation dataset (N = 1,310, years 2019–2020). RESULTS: SSI was diagnosed by an infection control specialist in 8.2, 5.2, and 31.2% of the patients in the training dataset who underwent hysterectomies, orthopedic surgeries and colorectal surgeries, respectively, vs. 6.2, 6.6, and 25.5%, respectively, in the validation dataset. The correlates of SSI after abdominal hysterectomy were prolonged hospitalization, ordering wound or blood culture, emergency room visit and reoperation; in orthopedic surgery, emergency room visit, wound culture, reoperation, and documentation of SSI, and in colorectal surgeries prolonged hospitalization, readmission, and ordering wound or blood cultures. Area under the curve was >90%. The sensitivity and specificity (95% CI) of the screening tool were 98% (88–100) and 58% (53–62), for abdominal hysterectomy, 91% (81–96) and 82% (80–84) in orthopedic surgeries and 96% (90–98) and 62% (58–66) in colorectal surgeries. The corresponding values for the validation dataset were 89% (67–97) and 75% (69–80) in abdominal hysterectomy; 85% (72–93) and 83% (80–86) in orthopedic surgeries and 98% (93–99) and 59% (53–64) in colorectal surgeries. The number of files needed to be fully reviewed declined by 61–66. CONCLUSION: The presented semi–automated simple screening tool for SSI surveillance had good sensitivity and specificity and it has great potential of reducing workload and improving SSI surveillance.
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spelling pubmed-99092722023-02-10 The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries Shitrit, Pnina Chowers, Michal Y. Muhsen, Khitam Front Med (Lausanne) Medicine BACKGROUND: Surveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults. METHODS: The training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal hysterectomies (N = 523) during 2015–2018. The gold standard for the validation of the screening tool was the presence of SSI as determined by a trained infection control practitioner, via manual full medical record review, using the US Center for Disease Control and Prevention criteria. Using multivariable regression models, we identified the correlates of SSI. Patients who had at least one of these correlates were classified as likely to having SSI and those who did not have any of the correlates were classified as unlikely to have SSI. We calculated the sensitivity and specificity of this tool compared to the gold standard and applied the tool to a validation dataset (N = 1,310, years 2019–2020). RESULTS: SSI was diagnosed by an infection control specialist in 8.2, 5.2, and 31.2% of the patients in the training dataset who underwent hysterectomies, orthopedic surgeries and colorectal surgeries, respectively, vs. 6.2, 6.6, and 25.5%, respectively, in the validation dataset. The correlates of SSI after abdominal hysterectomy were prolonged hospitalization, ordering wound or blood culture, emergency room visit and reoperation; in orthopedic surgery, emergency room visit, wound culture, reoperation, and documentation of SSI, and in colorectal surgeries prolonged hospitalization, readmission, and ordering wound or blood cultures. Area under the curve was >90%. The sensitivity and specificity (95% CI) of the screening tool were 98% (88–100) and 58% (53–62), for abdominal hysterectomy, 91% (81–96) and 82% (80–84) in orthopedic surgeries and 96% (90–98) and 62% (58–66) in colorectal surgeries. The corresponding values for the validation dataset were 89% (67–97) and 75% (69–80) in abdominal hysterectomy; 85% (72–93) and 83% (80–86) in orthopedic surgeries and 98% (93–99) and 59% (53–64) in colorectal surgeries. The number of files needed to be fully reviewed declined by 61–66. CONCLUSION: The presented semi–automated simple screening tool for SSI surveillance had good sensitivity and specificity and it has great potential of reducing workload and improving SSI surveillance. Frontiers Media S.A. 2023-01-26 /pmc/articles/PMC9909272/ /pubmed/36778736 http://dx.doi.org/10.3389/fmed.2023.1023385 Text en Copyright © 2023 Shitrit, Chowers and Muhsen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Shitrit, Pnina
Chowers, Michal Y.
Muhsen, Khitam
The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title_full The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title_fullStr The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title_full_unstemmed The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title_short The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
title_sort development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909272/
https://www.ncbi.nlm.nih.gov/pubmed/36778736
http://dx.doi.org/10.3389/fmed.2023.1023385
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