LPI can be potentially predicted based on donor and graft conditions. Accumulation of factors is correlated with an increased effect on LPI.

The CUSUM curve shows three phases in the learning and use of robotic assisted rectal cancer surgery which correspond to the phases of initial learning of the technique, consolidation and higher expertise or mastery. The data obtained suggest that the estimated learning curve for robotic assisted rectal cancer surgery is achieved after 21-23 cases.

Robotic advantages could have an impact on learning curve for rectal cancer and lower the number of cases that are necessary for rectal resections.

Everolimus may not be universally prescribed to prevent tumor recurrence in liver transplant patients with hepatocellular carcinoma. Future randomized trials should be focused on patients with histological features of increased tumor aggressiveness, in whom the potential benefit would be higher.

Summary Prognosis after liver transplantation depends on a combination of recipient and donor variables. The purpose of this study is to define an allocation system of steatotic donor livers relative to recipient model for end‐stage liver disease (MELD) score. We reviewed 500 consecutive OLT, computing the MELD score for each recipient. Fatty infiltration in grafts was categorized in no steatosis, 10–30%, 30–60% and ≥60% steatosis. MELD score did not affect preservation injury and graft dysfunction, which were increased with fat content. Recipient and graft survivals lowered when increasing MELD score. Outcome in low‐risk recipients (MELD ≤9) was not altered with steatosis, except those with ≥60%. Survival functions in moderate‐risk recipients (MELD 10–19) were moderately affected with 10–30% steatosis and severely with those with >30. Exactly 30–60% steatotic grafts work poorly in high‐risk recipients (MELD ≥20), and very poorly with ≥60% steatosis. Prognosis of candidates is optimally influenced when divergence of recipient–donor risks is presented.