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Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes

BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis. The diagnosis of SBP is still mostly based on ascites cultures and absolute ascites polymorphonuclear (PMN) cell count, which restricts the widely application in clinical settings. This study aim...

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Autores principales: Du, Tao, Li, Qing-ping, Jiang, Gui-xiang, Tan, Hui-yuan, Wu, Jiao-hua, Qin, Shan-yu, Yu, Bing, Jiang, Hai-xing, Luo, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640738/
https://www.ncbi.nlm.nih.gov/pubmed/37951894
http://dx.doi.org/10.1186/s12879-023-08731-w
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author Du, Tao
Li, Qing-ping
Jiang, Gui-xiang
Tan, Hui-yuan
Wu, Jiao-hua
Qin, Shan-yu
Yu, Bing
Jiang, Hai-xing
Luo, Wei
author_facet Du, Tao
Li, Qing-ping
Jiang, Gui-xiang
Tan, Hui-yuan
Wu, Jiao-hua
Qin, Shan-yu
Yu, Bing
Jiang, Hai-xing
Luo, Wei
author_sort Du, Tao
collection PubMed
description BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis. The diagnosis of SBP is still mostly based on ascites cultures and absolute ascites polymorphonuclear (PMN) cell count, which restricts the widely application in clinical settings. This study aimed to identify reliable and easy-to-use biomarkers for both diagnosis and prognosis of cirrhotic patients with SBP. METHODS: We conducted a retrospective study including 413 cirrhotic patients from March 2013 to July 2022 in the First Affiliated Hospital of Guangxi Medical University. Patients’ clinical characteristics and laboratory indices were collected and analyzed. Two machine learning methods (Xgboost and LASSO algorithms) and a logistic regression analysis were adopted to screen and validate the indices associated with the risk of SBP. A predictive model was constructed and validated using the estimated area under curve (AUC). The indices related to the survival of cirrhotic patients were also analyzed. RESULTS: A total of 413 cirrhotic patients were enrolled in the study, of whom 329 were decompensated and 84 were compensated. 52 patients complicated and patients with SBP had a poorer Child–Pugh score (P < 0.05). Patients with SBP had a greater proportion of malignancies than those without SBP(P < 0.05). The majority of laboratory test indicators differed significantly between patients with and without SBP (P < 0.05). Albumin, neutrophil-to-lymphocyte ratio (NLR), and ferritin-to-neutrophil ratio (FNR) were found to be independently associated with SBP in decompensated cirrhotic patients using LASSO algorithms, and logistic regression analysis. The model established by the three indices showed a high predictive value with an AUC of 0.808. Furthermore, increased neutrophils, ALP, and C-reactive protein-to-albumin ratio (CAR) were associated with the shorter survival time of patients with decompensated cirrhosis, and the combination of these indices showed a greater predictive value for cirrhotic patients. CONCLUSIONS: The present study identified FNR as a novel index in the diagnosis of SBP in decompensated patients with cirrhosis. A model based on neutrophils, ALP and CAR showed high performance in predicting the prognosis of patients with decompensated cirrhosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08731-w.
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spelling pubmed-106407382023-11-11 Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes Du, Tao Li, Qing-ping Jiang, Gui-xiang Tan, Hui-yuan Wu, Jiao-hua Qin, Shan-yu Yu, Bing Jiang, Hai-xing Luo, Wei BMC Infect Dis Research BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis. The diagnosis of SBP is still mostly based on ascites cultures and absolute ascites polymorphonuclear (PMN) cell count, which restricts the widely application in clinical settings. This study aimed to identify reliable and easy-to-use biomarkers for both diagnosis and prognosis of cirrhotic patients with SBP. METHODS: We conducted a retrospective study including 413 cirrhotic patients from March 2013 to July 2022 in the First Affiliated Hospital of Guangxi Medical University. Patients’ clinical characteristics and laboratory indices were collected and analyzed. Two machine learning methods (Xgboost and LASSO algorithms) and a logistic regression analysis were adopted to screen and validate the indices associated with the risk of SBP. A predictive model was constructed and validated using the estimated area under curve (AUC). The indices related to the survival of cirrhotic patients were also analyzed. RESULTS: A total of 413 cirrhotic patients were enrolled in the study, of whom 329 were decompensated and 84 were compensated. 52 patients complicated and patients with SBP had a poorer Child–Pugh score (P < 0.05). Patients with SBP had a greater proportion of malignancies than those without SBP(P < 0.05). The majority of laboratory test indicators differed significantly between patients with and without SBP (P < 0.05). Albumin, neutrophil-to-lymphocyte ratio (NLR), and ferritin-to-neutrophil ratio (FNR) were found to be independently associated with SBP in decompensated cirrhotic patients using LASSO algorithms, and logistic regression analysis. The model established by the three indices showed a high predictive value with an AUC of 0.808. Furthermore, increased neutrophils, ALP, and C-reactive protein-to-albumin ratio (CAR) were associated with the shorter survival time of patients with decompensated cirrhosis, and the combination of these indices showed a greater predictive value for cirrhotic patients. CONCLUSIONS: The present study identified FNR as a novel index in the diagnosis of SBP in decompensated patients with cirrhosis. A model based on neutrophils, ALP and CAR showed high performance in predicting the prognosis of patients with decompensated cirrhosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08731-w. BioMed Central 2023-11-11 /pmc/articles/PMC10640738/ /pubmed/37951894 http://dx.doi.org/10.1186/s12879-023-08731-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Du, Tao
Li, Qing-ping
Jiang, Gui-xiang
Tan, Hui-yuan
Wu, Jiao-hua
Qin, Shan-yu
Yu, Bing
Jiang, Hai-xing
Luo, Wei
Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title_full Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title_fullStr Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title_full_unstemmed Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title_short Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
title_sort systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640738/
https://www.ncbi.nlm.nih.gov/pubmed/37951894
http://dx.doi.org/10.1186/s12879-023-08731-w
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