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Würstle S, Hapfelmeier A, Karapetyan S, Studen F, Isaakidou A, Schneider T, Schmid RM, von Delius S, Gundling F, Burgkart R, Obermeier A, Mayr U, Ringelhan M, Rasch S, Lahmer T, Geisler F, Turner PE, Chan BK, Spinner CD, Schneider J. Differentiation of Spontaneous Bacterial Peritonitis from Secondary Peritonitis in Patients with Liver Cirrhosis: Retrospective Multicentre Study. Diagnostics (Basel) 2023; 13:diagnostics13050994. [PMID: 36900138 PMCID: PMC10000989 DOI: 10.3390/diagnostics13050994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/27/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023] Open
Abstract
Ascitic fluid infection is a serious complication of liver cirrhosis. The distinction between the more common spontaneous bacterial peritonitis (SBP) and the less common secondary peritonitis in patients with liver cirrhosis is crucial due to the varying treatment approaches. This retrospective multicentre study was conducted in three German hospitals and analysed 532 SBP episodes and 37 secondary peritonitis episodes. Overall, >30 clinical, microbiological, and laboratory parameters were evaluated to identify key differentiation criteria. Microbiological characteristics in ascites followed by severity of illness and clinicopathological parameters in ascites were the most important predictors identified by a random forest model to distinguish between SBP and secondary peritonitis. To establish a point-score model, a least absolute shrinkage and selection operator (LASSO) regression model selected the ten most promising discriminatory features. By aiming at a sensitivity of 95% either to rule out or rule in SBP episodes, two cut-off scores were defined, dividing patients with infected ascites into a low-risk (score ≥ 45) and high-risk group (score < 25) for secondary peritonitis. Overall, the discrimination of secondary peritonitis from SBP remains challenging. Our univariable analyses, random forest model, and LASSO point score may help clinicians with the crucial differentiation between SBP and secondary peritonitis.
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Affiliation(s)
- Silvia Würstle
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Department of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, CT 06520, USA
| | - Alexander Hapfelmeier
- Institute of General Practice and Health Services Research, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Institute of AI and Informatics in Medicine, School of Medicine, Technical University of Munich, Einsteinstr. 25, 81675 Munich, Germany
| | - Siranush Karapetyan
- Institute of AI and Informatics in Medicine, School of Medicine, Technical University of Munich, Einsteinstr. 25, 81675 Munich, Germany
| | - Fabian Studen
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Andriana Isaakidou
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Tillman Schneider
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Roland M. Schmid
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Stefan von Delius
- Department of Internal Medicine II, RoMed Hospital Rosenheim, Pettenkoferstr. 10, 83022 Rosenheim, Germany
| | - Felix Gundling
- Department of Gastroenterology, Hepatology, and Gastrointestinal Oncology, Bogenhausen Hospital of the Munich Municipal Hospital Group, Englschalkinger Straße 77, 81925 Munich, Germany
- Department of Internal Medicine II, Klinikum am Bruderwald, Sozialstiftung Bamberg, Buger Straße 80, 96049 Bamberg, Germany
| | - Rainer Burgkart
- Clinic of Orthopaedics and Sports Orthopaedics, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Andreas Obermeier
- Clinic of Orthopaedics and Sports Orthopaedics, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Ulrich Mayr
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Marc Ringelhan
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Sebastian Rasch
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Tobias Lahmer
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Fabian Geisler
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Paul E. Turner
- Department of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, CT 06520, USA
- Program in Microbiology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Benjamin K. Chan
- Department of Ecology and Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, CT 06520, USA
| | - Christoph D. Spinner
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Jochen Schneider
- Department of Internal Medicine II, University Hospital Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Ismaninger Str. 22, 81675 Munich, Germany
- Correspondence:
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Würstle S, Hapfelmeier A, Karapetyan S, Studen F, Isaakidou A, Schneider T, Schmid RM, von Delius S, Gundling F, Triebelhorn J, Burgkart R, Obermeier A, Mayr U, Heller S, Rasch S, Lahmer T, Geisler F, Chan B, Turner PE, Rothe K, Spinner CD, Schneider J. A Novel Machine Learning-Based Point-Score Model as a Non-Invasive Decision-Making Tool for Identifying Infected Ascites in Patients with Hydropic Decompensated Liver Cirrhosis: A Retrospective Multicentre Study. Antibiotics (Basel) 2022; 11:antibiotics11111610. [PMID: 36421254 PMCID: PMC9686825 DOI: 10.3390/antibiotics11111610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/06/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
This study is aimed at assessing the distinctive features of patients with infected ascites and liver cirrhosis and developing a scoring system to allow for the accurate identification of patients not requiring abdominocentesis to rule out infected ascites. A total of 700 episodes of patients with decompensated liver cirrhosis undergoing abdominocentesis between 2006 and 2020 were included. Overall, 34 clinical, drug, and laboratory features were evaluated using machine learning to identify key differentiation criteria and integrate them into a point-score model. In total, 11 discriminatory features were selected using a Lasso regression model to establish a point-score model. Considering pre-test probabilities for infected ascites of 10%, 15%, and 25%, the negative and positive predictive values of the point-score model for infected ascites were 98.1%, 97.0%, 94.6% and 14.9%, 21.8%, and 34.5%, respectively. Besides the main model, a simplified model was generated, containing only features that are fast to collect, which revealed similar predictive values. Our point-score model appears to be a promising non-invasive approach to rule out infected ascites in clinical routine with high negative predictive values in patients with hydropic decompensated liver cirrhosis, but further external validation in a prospective study is needed.
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Affiliation(s)
- Silvia Würstle
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
| | - Alexander Hapfelmeier
- Institute of General Practice and Health Services Research, School of Medicine, Technical University of Munich, 81667 Munich, Germany
- Institute of AI and Informatics in Medicine, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Siranush Karapetyan
- Institute of AI and Informatics in Medicine, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Fabian Studen
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Andriana Isaakidou
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Tillman Schneider
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Roland M. Schmid
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Stefan von Delius
- Department of Internal Medicine II, RoMed Hospital Rosenheim, 83022 Rosenheim, Germany
| | - Felix Gundling
- Department of Gastroenterology, Hepatology, and Gastrointestinal Oncology, Bogenhausen Hospital of the Munich Municipal Hospital Group, 81925 Munich, Germany
- Department of Internal Medicine II, Klinikum am Bruderwald, Sozialstiftung Bamberg, 96049 Bamberg, Germany
| | - Julian Triebelhorn
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Rainer Burgkart
- Clinic of Orthopaedics and Sports Orthopaedics, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Andreas Obermeier
- Clinic of Orthopaedics and Sports Orthopaedics, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Ulrich Mayr
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Stephan Heller
- Clinic of Orthopaedics and Sports Orthopaedics, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Sebastian Rasch
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Tobias Lahmer
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Fabian Geisler
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Benjamin Chan
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
| | - Paul E. Turner
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
- Program in Microbiology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kathrin Rothe
- Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Christoph D. Spinner
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, 81675 Munich, Germany
| | - Jochen Schneider
- Department of Internal Medicine II, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, 81675 Munich, Germany
- Correspondence:
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