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Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors

Minimal-invasive techniques are increasingly applied in clinical practice and have contributed towards improving postoperative outcomes. While comparing favorably with open surgery in terms of safety, the occurrence of severe complications remains a grave concern. To date, no objective predictive sy...

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Autores principales: Haber, Philipp K., Maier, Christoph, Kästner, Anika, Feldbrügge, Linda, Ortiz Galindo, Santiago Andres, Geisel, Dominik, Fehrenbach, Uli, Biebl, Matthias, Krenzien, Felix, Benzing, Christian, Schöning, Wenzel, Pratschke, Johann, Schmelzle, Moritz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916554/
https://www.ncbi.nlm.nih.gov/pubmed/33578875
http://dx.doi.org/10.3390/jcm10040685
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author Haber, Philipp K.
Maier, Christoph
Kästner, Anika
Feldbrügge, Linda
Ortiz Galindo, Santiago Andres
Geisel, Dominik
Fehrenbach, Uli
Biebl, Matthias
Krenzien, Felix
Benzing, Christian
Schöning, Wenzel
Pratschke, Johann
Schmelzle, Moritz
author_facet Haber, Philipp K.
Maier, Christoph
Kästner, Anika
Feldbrügge, Linda
Ortiz Galindo, Santiago Andres
Geisel, Dominik
Fehrenbach, Uli
Biebl, Matthias
Krenzien, Felix
Benzing, Christian
Schöning, Wenzel
Pratschke, Johann
Schmelzle, Moritz
author_sort Haber, Philipp K.
collection PubMed
description Minimal-invasive techniques are increasingly applied in clinical practice and have contributed towards improving postoperative outcomes. While comparing favorably with open surgery in terms of safety, the occurrence of severe complications remains a grave concern. To date, no objective predictive system has been established to guide clinicians in estimating complication risks as the relative contribution of general patient health, liver function and surgical parameters remain unclear. Here, we perform a single-center analysis of all consecutive patients undergoing laparoscopic liver resection for primary hepatic malignancies since 2010. Among the 210 patients identified, 32 developed major complications. Several independent predictors were identified through a multivariate analysis, defining a preoperative model: diabetes, history of previous hepatectomy, surgical approach, alanine aminotransferase levels and lesion entity. The addition of operative time and whether conversion was required significantly improved predictions and were thus incorporated into the postoperative model. Both models were able to identify patients with major complications with acceptable performance (area under the receiver-operating characteristic curve (AUC) for a preoperative model = 0.77 vs. postoperative model = 0.80). Internal validation was performed and confirmed the discriminatory ability of the models. An easily accessible online tool was deployed in order to estimate probabilities of severe complication without the need for manual calculation.
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spelling pubmed-79165542021-03-01 Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors Haber, Philipp K. Maier, Christoph Kästner, Anika Feldbrügge, Linda Ortiz Galindo, Santiago Andres Geisel, Dominik Fehrenbach, Uli Biebl, Matthias Krenzien, Felix Benzing, Christian Schöning, Wenzel Pratschke, Johann Schmelzle, Moritz J Clin Med Article Minimal-invasive techniques are increasingly applied in clinical practice and have contributed towards improving postoperative outcomes. While comparing favorably with open surgery in terms of safety, the occurrence of severe complications remains a grave concern. To date, no objective predictive system has been established to guide clinicians in estimating complication risks as the relative contribution of general patient health, liver function and surgical parameters remain unclear. Here, we perform a single-center analysis of all consecutive patients undergoing laparoscopic liver resection for primary hepatic malignancies since 2010. Among the 210 patients identified, 32 developed major complications. Several independent predictors were identified through a multivariate analysis, defining a preoperative model: diabetes, history of previous hepatectomy, surgical approach, alanine aminotransferase levels and lesion entity. The addition of operative time and whether conversion was required significantly improved predictions and were thus incorporated into the postoperative model. Both models were able to identify patients with major complications with acceptable performance (area under the receiver-operating characteristic curve (AUC) for a preoperative model = 0.77 vs. postoperative model = 0.80). Internal validation was performed and confirmed the discriminatory ability of the models. An easily accessible online tool was deployed in order to estimate probabilities of severe complication without the need for manual calculation. MDPI 2021-02-10 /pmc/articles/PMC7916554/ /pubmed/33578875 http://dx.doi.org/10.3390/jcm10040685 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Haber, Philipp K.
Maier, Christoph
Kästner, Anika
Feldbrügge, Linda
Ortiz Galindo, Santiago Andres
Geisel, Dominik
Fehrenbach, Uli
Biebl, Matthias
Krenzien, Felix
Benzing, Christian
Schöning, Wenzel
Pratschke, Johann
Schmelzle, Moritz
Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title_full Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title_fullStr Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title_full_unstemmed Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title_short Predicting the Risk of Postoperative Complications in Patients Undergoing Minimally Invasive Resection of Primary Liver Tumors
title_sort predicting the risk of postoperative complications in patients undergoing minimally invasive resection of primary liver tumors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7916554/
https://www.ncbi.nlm.nih.gov/pubmed/33578875
http://dx.doi.org/10.3390/jcm10040685
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