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Evolution of risk prediction models for post-operative mortality in patients with cirrhosis
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 di...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224863/ https://www.ncbi.nlm.nih.gov/pubmed/36971983 http://dx.doi.org/10.1007/s12072-023-10494-0 |
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author | Kalo, Eric George, Jacob Read, Scott Majumdar, Avik Ahlenstiel, Golo |
author_facet | Kalo, Eric George, Jacob Read, Scott Majumdar, Avik Ahlenstiel, Golo |
author_sort | Kalo, Eric |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10224863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-102248632023-05-29 Evolution of risk prediction models for post-operative mortality in patients with cirrhosis Kalo, Eric George, Jacob Read, Scott Majumdar, Avik Ahlenstiel, Golo Hepatol Int Consensus 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. Springer India 2023-03-27 /pmc/articles/PMC10224863/ /pubmed/36971983 http://dx.doi.org/10.1007/s12072-023-10494-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Consensus Kalo, Eric George, Jacob Read, Scott Majumdar, Avik Ahlenstiel, Golo Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title | Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title_full | Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title_fullStr | Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title_full_unstemmed | Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title_short | Evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
title_sort | evolution of risk prediction models for post-operative mortality in patients with cirrhosis |
topic | Consensus |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224863/ https://www.ncbi.nlm.nih.gov/pubmed/36971983 http://dx.doi.org/10.1007/s12072-023-10494-0 |
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