ArticleFrontiers in medicine2021
Establishment and Validation of a Non-Invasive Diagnostic Nomogram to Identify Spontaneous Bacterial Peritonitis in Patients With Decompensated Cirrhosis.
Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Comparison of the Diagnostic Accuracies of Procalcitonin and C-Reactive Protein for Spontaneous Bacterial Peritonitis in Patients with Cirrhosis: A Systematic Review and Meta-Analysis.Medicina (Kaunas, Lithuania) · 2025Pooled it
- Early risk stratification of sepsis-related liver injury via machine learning: a multicohort study.Frontiers in medicine · 2026Article
- Exploring the next frontier in diagnosing spontaneous bacterial peritonitis.World journal of hepatology · 2025Article
- Predictive Factors and Nomogram for Spontaneous Bacterial Peritonitis in Decompensated Cirrhosis Among the Elderly.Journal of inflammation research · 2024Article
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8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSpontaneous bacterial peritonitis (SBP) is a common and life-threatening infection in patients with decompensated cirrhosis (DC), and it is accompanied with high mortality and morbidity. However, early diagnosis of spontaneous bacterial peritonitis (SBP) is not possible because of the lack of typical symptoms or the low patient compliance and positivity rate of the ascites puncture test. We aimed to establish and validate a non-invasive diagnostic nomogram to identify SBP in patients with DC.
methodData were collected from 4,607 patients with DC from July 2015 to December 2019 in two tertiary hospitals in Chongqing, China (A and B). Patients with DC were divided into the SBP group (995 cases) and the non-SBP group (3,612 cases) depending on whether the patients had SBP during hospitalization. About 70% (2,685 cases) of patients in hospital A were randomly selected as the traindata, and the remaining 30% (1,152 cases) were used as the internal validation set. Patients in hospital B (770 cases) were used as the external validation set. The univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to screen variables, and logistic regression was used to determine independent predictors to construct a nomogram to identify patients with SBP. Area under curve (AUC), calibration curve, and dynamic component analysis (DCA) were carried out to determine the effectiveness of the nomogram.
resultThe nomogram was composed of seven variables, namely, mean red blood cell hemoglobin concentration (odds ratio [
conclusionThis study identified the independent risk factors of SBP in patients with DC and used them to construct a nomogram, which may provide clinical reference information for the diagnosis of SBP in patients with DC.
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