AI Article Synopsis
- Liver resection is a high-risk procedure, and predicting its morbidity and mortality rates using various models is crucial for patient safety.
- Research was conducted using multiple databases to find relevant studies, resulting in the inclusion of 34 papers published before August 2012.
- While several existing models like MELD and APACHE II can help predict outcomes after liver surgery, there is currently no effective scoring system for surgical complications due to a lack of validation.
Article Abstract
Background: Liver resection is still a risky procedure with high morbidity and mortality. It is significant to predict the morbidity and mortality with some models after liver resection.
Data Sources: The MEDLINE/PubMed, Web of Science, Google Scholar, and Cochrane Library databases were searched using the terms "hepatectomy" and "risk assessment" for relevant studies before August 2012. Papers published in English were included.
Results: Thirty-four original papers were included finally. Some models, such as MELD, APACHE II, E-PASS, or POSSUM, widely used in other populations, are useful to predict the morbidity and mortality after liver resection. Some special models for liver resection are used to predict outcomes after liver resection, such as mortality, liver dysfunction, transfusion, or acute renal failure. However, there is no good scoring system to predict or classify surgical complications because of shortage of internal or external validation.
Conclusion: It is important to validate the models for the major complications after liver resection with further internal or external databases.
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| http://dx.doi.org/10.1016/s1499-3872(13)60075-2 | DOI Listing |
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