Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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
_version_ 1784782371522871296
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
work_keys_str_mv AT wiesematsl identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT urbansteffi identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT vonrheinbabensabrina identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT frostfabian identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT sendlermatthias identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT weissfrankulrich identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT bulowrobin identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT kromreymarieluise identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT tranquangtrung identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT lerchmarkusm identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT schauerbirgit identificationofearlypredictorsforinfectednecrosisinacutepancreatitis
AT aghdassialia identificationofearlypredictorsforinfectednecrosisinacutepancreatitis