Factors that predict recurrent spontaneous bacterial peritonitis in cirrhotic patients

Termsinsuk, Panotpol; Auesomwang, Chonticha

doi:10.1111/ijcp.13457

Cited by 4 publications

(2 citation statements)

References 36 publications

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“…Interestingly, in this study, NLR was the most important predictor for infection in DC patients, indicating that NLR’s sensitivity in predicting infection seems to be superior to blood neutrophil percentage. In addition, in this study, all six features included in the simple-tree XGBoost model have appeared in other studies on constructing prediction model for infection in patients with liver cirrhosis, indicating that the six features selected in this study have high clinical practicality in predicting infection [ 34 – 37 ].…”

Section: Discussionmentioning

confidence: 79%

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012–2021) Multicenter Retrospective Case-control study

Zheng,

Li,

Zhang

et al. 2023

BMC Gastroenterol

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Objectives To appraise effective predictors for infection in patients with decompensated cirrhosis (DC) by using XGBoost algorithm in a retrospective case-control study. Methods Clinical data were retrospectively collected from 6,648 patients with DC admitted to five tertiary hospitals. Indicators with significant differences were determined by univariate analysis and least absolute contraction and selection operator (LASSO) regression. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed infection risk prediction model with simple-tree XGBoost model. Finally, the simple-tree XGBoost model is compared with the traditional logical regression (LR) model. Performances of models were evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. Results Six features, including total bilirubin, blood sodium, albumin, prothrombin activity, white blood cell count, and neutrophils to lymphocytes ratio were selected as predictors for infection in patients with DC. Simple-tree XGBoost model conducted by these features can predict infection risk accurately with an AUROC of 0.971, sensitivity of 0.915, and specificity of 0.900 in training set. The performance of simple-tree XGBoost model is better than that of traditional LR model in training set, internal verification set, and external feature set (P < 0.001). Conclusions The simple-tree XGBoost predictive model developed based on a minimal amount of clinical data available to DC patients with restricted medical resources could help primary healthcare practitioners promptly identify potential infection.

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Section: Discussionmentioning

confidence: 79%

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012–2021) Multicenter Retrospective Case-control study

Zheng,

Li,

Zhang

et al. 2023

BMC Gastroenterol

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“…By comparison, a restrictive human albumin infusion strategy is often employed in previous studies and our clinical practice, because only a very low serum albumin concentration would significantly increase mortality. For example, serum albumin concentration ≤20 g/L was significantly associated with a higher risk of spontaneous bacterial peritonitis recurrence in liver cirrhosis (7), and human albumin infusion improved the survival of spontaneous bacterial peritonitis (8). Additionally, serum albumin concentration ≤22.8 g/L was an independent risk factor for death in liver cirrhosis with hepatic encephalopathy, and human albumin infusion decreased the in-hospital mortality of patients with hepatic encephalopathy (9,10).…”

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confidence: 99%

Human albumin infusion strategy in liver cirrhosis: liberal or restrictive?

Bai¹,

Cheng²,

Méndez-Sánchez³

et al. 2021

Ann Transl Med

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A risk score to predict 30-day hospital readmission rate in cirrhotic patients with spontaneous bacterial peritonitis

Mousa,

Abdel-Razik,

Elbaz

et al. 2023

Eur J Med Res

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Background and aim There is lack of 30-day hospital readmission prediction score in patients with liver cirrhosis and SBP. The aim of this study is to recognize factors capable of predicting 30-day readmission and to develop a readmission risk score in patients with SBP. Methods This study prospectively examined the 30-day hospital readmission for patients previously discharged with a diagnosis of SBP. Based on index hospitalization variables, a multivariable logistic regression model was implemented to recognize predictors of patient hospital readmission within 30 days. Consequently, Mousa readmission risk score was established to predict 30-day hospital readmission. Results Of 475 patients hospitalized with SBP, 400 patients were included in this study. The 30-day readmission rate was 26.5%, with 16.03% of patients readmitted with SBP. Age ≥ 60, MELD > 15, serum bilirubin > 1.5 mg/dL, creatinine > 1.2 mg/dL, INR > 1.4, albumin < 2.5 g/dL, platelets count ≤ 74 (103/dL) were found to be independent predictors of 30-day readmission. Incorporating these predictors, Mousa readmission score was established to predict 30-day patient readmissions. ROC curve analysis demonstrated that at a cutoff value ≥ 4, Mousa score had optimum discriminative power for predicting the readmission in SBP with sensitivity 90.6% and specificity 92.9%. However, at cutoff value ≥ 6 the sensitivity and specificity were 77.4% and 99.7%, respectively, while a cutoff value ≥ 2 had sensitivity of 99.1% and specificity of 31.6%. Conclusions The 30-day readmission rate of SBP was 25.6%. With the suggested simple risk assessment Mousa score, patients at high risk for early readmission can be easily identified so as to possibly prevent poorer outcomes.

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Factors that predict recurrent spontaneous bacterial peritonitis in cirrhotic patients

Cited by 4 publications

References 36 publications

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012–2021) Multicenter Retrospective Case-control study

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012–2021) Multicenter Retrospective Case-control study

Human albumin infusion strategy in liver cirrhosis: liberal or restrictive?

A risk score to predict 30-day hospital readmission rate in cirrhotic patients with spontaneous bacterial peritonitis

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