Prognostic Factors for Survival in Patients with Liver Cirrhosis

Samada, Marcia; Hernández, Julio César

doi:10.5772/30184

Cited by 4 publications

(4 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…7 This result is also considered much lower than other result obtained from different studies in several countries; such as 85% in England and Cuba with 65%. 3,8 This study aims to analyze the survival rate of liver cirrhotic patients in each Child Pugh classification. From the graph we can see that the survival rate between CP A and B; also between CP A and C is significantly different.…”

Section: Discussionmentioning

confidence: 99%

“…1 Child Pugh scoring system and MELD has long been well established as a prognostic predictor of severity and mortality in liver cirrhotic patients as seen in several studies. 2,3,4 In these studies, CP scoring especially has been shown to accurately predict the mortality outcome of liver cirrhotic patient with 2-year survival rate of 90%, 70%, and 38% for CP class A, B, and C, respectively. 2 MELD score in the other hand has been proven good for predicting the 3-month mortality of liver cirrhotic patients.…”

Section: Introductionmentioning

confidence: 99%

“…2 MELD score in the other hand has been proven good for predicting the 3-month mortality of liver cirrhotic patients. 3 The preferences to use between MELD and CP has long been a wide discussion. 5 In Indonesia, clinicians have long adopted these prognostic predictors and using it for assessment of their liver cirrhotic patients.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Survival Analysis of Hospitalized Liver Cirrhotic Patients in Jakarta: 2 Years Follow Up Study

Gani¹

2021

InaJGHE

View full text Add to dashboard Cite

Background: The incidence of liver cirrhosis in Indonesia is increasing over time. In this study, we aim to present a 2-year survival analysis on liver cirrhotic patients using Child-Pugh and MELD score and also analyzing the most common cause of death among liver cirrhotic patients.Method: A retrospective cohort study was used by evaluating the medical records of patients who went to internal medicine ward of Cipto Mangunkusumo Hospital during the period between 2011-2016. The inclusion criteria were all cirrhotic patient registered with a completely filled medical record. The exclusion criteria were the presence of Hepatocellular carcinoma, cholangiocarcinoma, and other form of malignanciesResults: A total of 89 patients were included in this study. The total of 75.3% of the patients were dead during the 2 years follow up with the most prevalent cause of death (COD) being infection (45.5%). Survival analysis, showed that the survival of CP Class A were significantly better than B and C. The cut off value for 2-years mortality was CP score 7 and MELD score 9 in liver cirrhotic patientsConclusion: The mortality rate of liver cirrhotic patients is very high with infection as the main COD. Patients with Child-Pugh score B and C have worse prognosis than Child-Pugh score A.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Survival Analysis of Hospitalized Liver Cirrhotic Patients in Jakarta: 2 Years Follow Up Study

Gani¹

2021

InaJGHE

View full text Add to dashboard Cite

show abstract

“…[12], on comparing CTP to the MELD scale, CTP was found to be more accurate in discriminating patients with liver cirrhosis than the MELD score in univariate logistic regression analysis (OR 21.54, AUC 0.770 vs. OR 5.17, AUC 0.684). These two scales are often presented as methods to show the long-term survival rate (where CTP seems to have a more predictive value than MELD); however, there are studies [12, 13] suggesting that the MELD score has an advantage over the CTP scale in evaluating short-term survival rate [13]. Nevertheless, it should be noted that the results from this study do not confirm that MELD as a single score has a better discrimination value than CTP.…”

Section: Discussionmentioning

confidence: 99%

Predictive power of Model for End-Stage Liver Disease and Child-Turcotte-Pugh score for mortality in cirrhotic patients

Piotrowski

Sączewska-Piotrowska

Jaroszewicz

et al. 2018

ceh

View full text Add to dashboard Cite

Aim of the studyTo assess the performance of Child-Turcotte-Pugh (CTP) and Model for End-Stage Liver Disease (MELD) scores’ kinetics during hospitalization in predicting in-hospital mortality in patients with liver cirrhosis.Material and methodsOne hundred and seventy-four cases of hospitalized liver cirrhosis patients were selected. The diagnosis of cirrhosis was made based on clinical, biochemical, ultrasonic, histological, and endoscopic findings and results. CTP and MELD scores at admission and ΔCTP and ΔMELD were calculated. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curve analysis were performed. In the models, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The area under the ROC curve (AUC) was used to measure the accuracy. For the optimal cutoff point, sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were calculated. The Kaplan-Meier method was used to construct survival curves, and the log-rank test was used to compare time to death, with respect to MELD and CTP categories.ResultsAmong the assessed scores, the highest area under the ROC curve (AUC) in univariate logistic regression analysis was calculated for ΔMELD ≥ 1, followed by ΔCTP ≥ 1, CTP > 8, and MELD > 17. Based on the selected criteria, multivariate models were created that were characterized by an outstanding ability to predict the in-hospital mortality.ConclusionsIn-hospital mortality is relatively high in patients with liver cirrhosis. The combination of CTP and MELD scoring methods, combined with their kinetics, allows for the prediction of short-term mortality.

show abstract

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression

Perveen

Shahbaz

Keshavjee

et al. 2018

Sci Rep

View full text Add to dashboard Cite

Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screening is complicated by the fact that the accuracy of noninvasive testing lacks specificity and sensitivity to make and stage the diagnosis. Currently no non-invasive ATP III criteria based prediction method is available to diagnose NAFLD risk. Firstly, the objective of this research is to develop machine learning based method in order to identify individuals at an increased risk of developing NAFLD using risk factors of ATP III clinical criteria updated in 2005 for Metabolic Syndrome (MetS). Secondly, to validate the relative ability of quantitative score defined by Italian Association for the Study of the Liver (IASF) and guideline explicitly defined for the Canadian population based on triglyceride thresholds to predict NAFLD risk. We proposed a Decision Tree based method to evaluate the risk of developing NAFLD and its progression in the Canadian population, using Electronic Medical Records (EMRs) by exploring novel risk factors for NAFLD. Our results show proposed method could potentially help physicians make more informed choices about their management of patients with NAFLD. Employing the proposed application in ordinary medical checkup is expected to lessen healthcare expenditures compared with administering additional complicated test.

show abstract

Prognostic Factors for Survival in Patients with Liver Cirrhosis

Cited by 4 publications

References 60 publications

Survival Analysis of Hospitalized Liver Cirrhotic Patients in Jakarta: 2 Years Follow Up Study

Survival Analysis of Hospitalized Liver Cirrhotic Patients in Jakarta: 2 Years Follow Up Study

Predictive power of Model for End-Stage Liver Disease and Child-Turcotte-Pugh score for mortality in cirrhotic patients

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression

Contact Info

Product

Resources

About