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A Validated Composite Score Demonstrates Potential Superiority to MELD-Based Systems in Predicting Short-Term Survival in Patients with Liver Cirrhosis and Spontaneous Bacterial Peritonitis—A Preliminary Study

Authors :
Yan-Ting Lin
Wei-Ting Chen
Tsung-Han Wu
Yu Liu
Li-Tong Liu
Wei Teng
Yi-Chung Hsieh
Yen-Mu Wu
Chien-Hao Huang
Chao-Wei Hsu
Rong-Nan Chien
Source :
Diagnostics, Vol 13, Iss 15, p 2578 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Background: Spontaneous bacterial peritonitis (SBP) is a severe complication in cirrhosis patients with ascites, leading to high mortality rates if not promptly treated. However, specific prediction models for SBP are lacking. Aims: This study aimed to compare commonly used cirrhotic prediction models (CTP score, MELD, MELD-Na, iMELD, and MELD 3.0) for short-term mortality prediction and develop a novel model to improve mortality prediction. Methods: Patients with the first episode of SBP were included. Prognostic values for mortality were assessed using AUROC analysis. A novel prediction model was developed and validated. Results: In total, 327 SBP patients were analyzed, with HBV infection as the main etiologies. MELD 3.0 demonstrated the highest AUROC among the traditional models. The novel model, incorporating HRS, exhibited superior predictive accuracy for in-hospital in all patients and 3-month mortality in HBV-cirrhosis, with AUROC values of 0.827 and 0.813 respectively, surpassing 0.8. Conclusions: MELD 3.0 score outperformed the CTP score and showed a non-significant improvement compared to other MELD-based scores, while the novel SBP model demonstrated impressive accuracy. Internal validation and an HBV-related cirrhosis subgroup sensitivity analysis supported these findings, highlighting the need for a specific prognostic model for SBP and the importance of preventing HRS development to improve SBP prognosis.

Details

Language :
English
ISSN :
20754418
Volume :
13
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.4f824b4246f44378a0dcf6700428943b
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics13152578