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ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 38 Issue 11
Nov.  2022
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Article Navigation >  Journal of Clinical Hepatology  > 2022  >  38(11): 2499-2504

Establishment of a model for predicting the efficacy of third-generation cephalosporin in treatment of community-acquired spontaneous bacterial peritonitis

DOI: 10.3969/j.issn.1001-5256.2022.11.012
  • 1a.

    Department of Liver Disease, The Ninth Hospital of Nanchang, Nanchang 330002, China

  • 1b.

    Department of Information Technology, The Ninth Hospital of Nanchang, Nanchang 330002, China

  • 2.

    Department of Digestion, Children's Hospital of Jiangxi Province, Nanchang 330000, China

Research funding:

Key Research and Development Program of Jiangxi Province (20181BBG78010)

More Information
  • Corresponding author: ZHU Longchuan, zlcy1984@sina.com(ORCID: 0000-0002-4461-6195)
  • Received Date: 2022-04-05
  • Accepted Date: 2022-05-07
  • Published Date: 2022-11-20
    Abstract
  •   Objective  To investigate the factors for predicting the efficacy of third-generation cephalosporin (3rd GC) in the treatment of community-acquired spontaneous bacterial peritonitis (CASBP), and to establish and validate an efficacy predictive model for 3rd GC in the treatment of CASBP.  Methods  A retrospective analysis was performed for the clinical data of the patients with liver cirrhosis and CASBP who received 3rd GC monotherapy for initial treatment in The Ninth Hospital of Nanchang, and according to their treatment outcome, they were divided into non-response group and response group. The patients hospitalized from 2013 to 2018 were included in the modeling cohort (55 patients the non-response group and 110 in the response group), and those hospitalized from 2019 to 2020 were included in the validation cohort (17 patients in the non-response group and 43 in the response group). In the modeling cohort, the two groups were compared in terms of the indices including general information, underlying diseases, past history, clinical manifestation, and laboratory test results. Univariate analyses (the t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test or the Fisher's exact test was used for comparison of categorical data between groups) and a binary Logistic regression analysis were used to identify efficacy predictors, and an efficacy predictive model was established based on the logistic regression equation. The receiver operating characteristic (ROC) curve was plotted to perform internal and external validations of the model in the modeling cohort and the validation cohort, respectively.  Results  The study population had a mean age of 51.6±12.0 years, and male patients accounted for 80.0%; hepatitis B was the main cause of liver cirrhosis (66.7%), and 3rd GC had an overall response rate of 68.0%. In the modeling cohort, compared with the response group, the non-response group had significantly lower proportion of patients with the first onset of SBP, polymorphonuclear (PMN) count in ascites, and leukocyte count in ascites (all P < 0.05), as well as significantly higher proportion of patients with exposure to broad-spectrum antibiotic and platelet count (both P < 0.05). The Logistic regression analysis showed that the first onset of SBP (odds ratio [OR]=0.158, 95% confidence interval [CI]: 0.064-0.392, P < 0.001), ascites PMN count (OR=0.728, 95%CI: 0.530-0.998, P=0.046), exposure to broad-spectrum antibiotic (OR=9.152, 95%CI: 1.513-55.351, P=0.016), and platelet count (OR=1.012, 95%CI: 1.006-1.019, P < 0.001) were independent predictive factors for non-response to 3rd GC. The efficacy predictive model had an area under the ROC curve (AUC) of 0.840, and based on the maximum Youden index, predictive score ≥ 0.207 was the optimal cut-off value for predicting non-response, with a corresponding Youden index of 0.536, a sensitivity of 89.1%, a specificity of 63.6%, a positive predictive value of 55.1%, and a negative predictive value of 92.1%. This model had an AUC of 0.837 in the validation cohort.  Conclusion  The first onset of SBP and higher ascites PMN count are the protective factors against non-response to 3rd GC for the treatment of CASBP, and exposure to broad-spectrum antibiotic and higher platelet count are the risk factors for such non-response. The model established for predicting the efficacy of 3rd GC in the treatment of CASBP has good predictive performance and thus holds promise for clinical application.

     

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