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Identification of early predictors for infected necrosis in acute pancreatitis
BACKGROUND: In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet. ME...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440524/ https://www.ncbi.nlm.nih.gov/pubmed/36057565 http://dx.doi.org/10.1186/s12876-022-02490-9 |
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author | Wiese, Mats L. Urban, Steffi von Rheinbaben, Sabrina Frost, Fabian Sendler, Matthias Weiss, Frank Ulrich Bülow, Robin Kromrey, Marie-Luise Tran, Quang Trung Lerch, Markus M. Schauer, Birgit Aghdassi, Ali A. |
author_facet | Wiese, Mats L. Urban, Steffi von Rheinbaben, Sabrina Frost, Fabian Sendler, Matthias Weiss, Frank Ulrich Bülow, Robin Kromrey, Marie-Luise Tran, Quang Trung Lerch, Markus M. Schauer, Birgit Aghdassi, Ali A. |
author_sort | Wiese, Mats L. |
collection | PubMed |
description | BACKGROUND: In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet. METHODS: This study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score. RESULTS: We identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547–0.809]), and a specificity of 0.840 (95%-CI [0.631–0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable. CONCLUSION: A model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02490-9. |
format | Online Article Text |
id | pubmed-9440524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94405242022-09-04 Identification of early predictors for infected necrosis in acute pancreatitis Wiese, Mats L. Urban, Steffi von Rheinbaben, Sabrina Frost, Fabian Sendler, Matthias Weiss, Frank Ulrich Bülow, Robin Kromrey, Marie-Luise Tran, Quang Trung Lerch, Markus M. Schauer, Birgit Aghdassi, Ali A. BMC Gastroenterol Research BACKGROUND: In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet. METHODS: This study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score. RESULTS: We identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547–0.809]), and a specificity of 0.840 (95%-CI [0.631–0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable. CONCLUSION: A model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02490-9. BioMed Central 2022-09-03 /pmc/articles/PMC9440524/ /pubmed/36057565 http://dx.doi.org/10.1186/s12876-022-02490-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wiese, Mats L. Urban, Steffi von Rheinbaben, Sabrina Frost, Fabian Sendler, Matthias Weiss, Frank Ulrich Bülow, Robin Kromrey, Marie-Luise Tran, Quang Trung Lerch, Markus M. Schauer, Birgit Aghdassi, Ali A. Identification of early predictors for infected necrosis in acute pancreatitis |
title | Identification of early predictors for infected necrosis in acute pancreatitis |
title_full | Identification of early predictors for infected necrosis in acute pancreatitis |
title_fullStr | Identification of early predictors for infected necrosis in acute pancreatitis |
title_full_unstemmed | Identification of early predictors for infected necrosis in acute pancreatitis |
title_short | Identification of early predictors for infected necrosis in acute pancreatitis |
title_sort | identification of early predictors for infected necrosis in acute pancreatitis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440524/ https://www.ncbi.nlm.nih.gov/pubmed/36057565 http://dx.doi.org/10.1186/s12876-022-02490-9 |
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