Risk assessment in patients undergoing liver resection

Area of Science:

• Hepatobiliary Surgery
• Surgical Risk Assessment
• Medical Informatics

Background:

• Liver resection carries significant risks, including high morbidity and mortality rates.
• Accurate prediction of patient outcomes post-hepatectomy is essential for clinical decision-making.

Purpose of the Study:

• To review existing risk assessment models for predicting morbidity and mortality after liver resection.
• To identify the limitations of current models in classifying surgical complications.

Main Methods:

• A systematic literature search was conducted across major databases (MEDLINE/PubMed, Web of Science, Google Scholar, Cochrane Library) up to August 2012.
• Keywords used included "hepatectomy" and "risk assessment".
• Included studies were published in English.

Main Results:

• Thirty-four original papers were analyzed.
• General risk assessment models (MELD, APACHE II, E-PASS, POSSUM) and liver-specific models demonstrated utility in predicting outcomes like mortality and liver dysfunction.
• No validated scoring system effectively predicts or classifies surgical complications due to a lack of internal/external validation.

Conclusions:

• Existing risk models offer some predictive value for liver resection outcomes.
• Further internal and external validation of models is imperative for accurate prediction of major complications following hepatectomy.