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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-7916554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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