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External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence
PURPOSE: Postoperative pancreatic fistula (POPF) is a life-threatening complication following pancreatoduodenectomy (PD). We previously developed nomogram- and artificial intelligence (AI)-based risk prediction platforms for POPF after PD. This study aims to externally validate these platforms. METH...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Korean Surgical Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914522/ https://www.ncbi.nlm.nih.gov/pubmed/35317357 http://dx.doi.org/10.4174/astr.2022.102.3.147 |
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author | Yoon, So Jeong Kwon, Wooil Lee, Ok Joo Jung, Ji Hye Shin, Yong Chan Lim, Chang-Sup Kim, Hongbeom Jang, Jin-Young Shin, Sang Hyun Heo, Jin Seok Han, In Woong |
author_facet | Yoon, So Jeong Kwon, Wooil Lee, Ok Joo Jung, Ji Hye Shin, Yong Chan Lim, Chang-Sup Kim, Hongbeom Jang, Jin-Young Shin, Sang Hyun Heo, Jin Seok Han, In Woong |
author_sort | Yoon, So Jeong |
collection | PubMed |
description | PURPOSE: Postoperative pancreatic fistula (POPF) is a life-threatening complication following pancreatoduodenectomy (PD). We previously developed nomogram- and artificial intelligence (AI)-based risk prediction platforms for POPF after PD. This study aims to externally validate these platforms. METHODS: Between January 2007 and December 2016, a total of 1,576 patients who underwent PD in Seoul National University Hospital, Ilsan Paik Hospital, and Boramae Medical Center were retrospectively reviewed. The individual risk scores for POPF were calculated using each platform by Samsung Medical Center. The predictive ability was evaluated using a receiver operating characteristic curve and the area under the curve (AUC). The optimal predictive value was obtained via backward elimination in accordance with the results from the AI development process. RESULTS: The AUC of the nomogram after external validation was 0.679 (P < 0.001). The values of AUC after backward elimination in the AI model varied from 0.585 to 0.672. A total of 13 risk factors represented the maximal AUC of 0.672 (P < 0.001). CONCLUSION: We performed external validation of previously developed platforms for predicting POPF. Further research is needed to investigate other potential risk factors and thereby improve the predictability of the platform. |
format | Online Article Text |
id | pubmed-8914522 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Korean Surgical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-89145222022-03-21 External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence Yoon, So Jeong Kwon, Wooil Lee, Ok Joo Jung, Ji Hye Shin, Yong Chan Lim, Chang-Sup Kim, Hongbeom Jang, Jin-Young Shin, Sang Hyun Heo, Jin Seok Han, In Woong Ann Surg Treat Res Original Article PURPOSE: Postoperative pancreatic fistula (POPF) is a life-threatening complication following pancreatoduodenectomy (PD). We previously developed nomogram- and artificial intelligence (AI)-based risk prediction platforms for POPF after PD. This study aims to externally validate these platforms. METHODS: Between January 2007 and December 2016, a total of 1,576 patients who underwent PD in Seoul National University Hospital, Ilsan Paik Hospital, and Boramae Medical Center were retrospectively reviewed. The individual risk scores for POPF were calculated using each platform by Samsung Medical Center. The predictive ability was evaluated using a receiver operating characteristic curve and the area under the curve (AUC). The optimal predictive value was obtained via backward elimination in accordance with the results from the AI development process. RESULTS: The AUC of the nomogram after external validation was 0.679 (P < 0.001). The values of AUC after backward elimination in the AI model varied from 0.585 to 0.672. A total of 13 risk factors represented the maximal AUC of 0.672 (P < 0.001). CONCLUSION: We performed external validation of previously developed platforms for predicting POPF. Further research is needed to investigate other potential risk factors and thereby improve the predictability of the platform. The Korean Surgical Society 2022-03 2022-03-04 /pmc/articles/PMC8914522/ /pubmed/35317357 http://dx.doi.org/10.4174/astr.2022.102.3.147 Text en Copyright © 2022, the Korean Surgical Society https://creativecommons.org/licenses/by-nc/4.0/Annals of Surgical Treatment and Research is an Open Access Journal. All articles are distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Yoon, So Jeong Kwon, Wooil Lee, Ok Joo Jung, Ji Hye Shin, Yong Chan Lim, Chang-Sup Kim, Hongbeom Jang, Jin-Young Shin, Sang Hyun Heo, Jin Seok Han, In Woong External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title | External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title_full | External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title_fullStr | External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title_full_unstemmed | External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title_short | External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
title_sort | external validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914522/ https://www.ncbi.nlm.nih.gov/pubmed/35317357 http://dx.doi.org/10.4174/astr.2022.102.3.147 |
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