Add like
Add dislike
Add to saved papers

Risk stratification of decompensated cirrhosis patients by Chronic Liver Failure Consortium scores: Classification and regression tree analysis.

AIM: Decompensated cirrhosis patients have greatly variable prognosis. The aim of the study was to carry out a risk stratification for those patients by Chronic Liver Failure (CLIF) Consortium scores.

METHODS: The performance of CLIF Consortium acute-on-chronic liver failure scores (CLIF-C ACLFs) and CLIF Consortium Acute Decompensation scores (CLIF-C ADs) were validated in 209 patients with ACLF and 1245 patients without ACLF at admission from the Ningbo Cohort. A classification and regression tree (CRT) analysis by CLIF-C ACLFs/CLIF-C ADs was carried out to stratify death risk among patients.

RESULTS: The CLIF-C ACLFs and CLIF-C ADs showed higher predictive accuracy than Model for End-stage Liver Disease (MELD) scores, MELD plus serum sodium (MELD-Na) scores, and Child-Turcotte-Pugh classification (CP) at main time points (28, 90, 180, and 365 days), determined by area under the receiver-operating characteristic curve and concordance index in ACLF and no-ACLF patients at admission. The CRT analysis categorized ACLF patients into two groups (advanced and early ACLF), and no-ACLF patients into three groups (high-, medium-, and low-risk AD) according to risk of death. However, early ACLF and high-risk AD patients had comparable mortality at the main time points. The CRT model had a higher area under the receiver-operating characteristic curve than MELDs, MELD-Nas, and CPs in predicting prognosis in all patients.

CONCLUSIONS: The CLIF-C ACLF and CLIF-C AD are better prognostic scores than MELD, MELD-Na, and CP in predicting mortality of ACLF and no-ACLF patients. A combined use of CLIF- Sequential Organ Failure Assessment, CLIF-C ACLFs, and CLIF-C ADs could identify cirrhosis patients at high death risk and assist clinical decisions for management.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app