Evolution of risk prediction models for post-operative mortality in patients with cirrhosis

Eric Kalo, Jacob George, Scott Read, Avik Majumdar, Golo Ahlenstiel

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The perception of high surgical risk among patients with cirrhosis has resulted in a long-standing reluctance to operate. Risk stratification tools, first implemented over 60 years ago, have attempted to assess mortality risk among cirrhotic patients and ensure the best possible outcomes for this difficult to treat cohort. Existing postoperative risk prediction tools including the Child–Turcotte–Pugh (CTP) and Model for End-stage Liver Disease (MELD) provide some prediction of risk in counselling patients and their families but tend to overestimate surgical risk. More personalised prediction algorithms such as the Mayo Risk Score and VOCAL-Penn score that incorporate surgery-specific risks have demonstrated a significant improvement in prognostication and can ultimately aid multidisciplinary team determination of potential risks. The development of future risk scores will need to incorporate, first and foremost, predictive efficacy, but perhaps just as important is the feasibility and usability by front-line healthcare professionals to ensure timely and efficient prediction of risk for cirrhotic patients.
Original languageEnglish
Pages (from-to)542-545
Number of pages4
JournalHepatology International
Volume17
Issue number3
DOIs
Publication statusPublished - Jun 2023

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