Famularo, Simone

Objective: To compare minimally invasive (MILR) and open liver resections (OLRs) for hepatocellular carcinoma (HCC) in patients with metabolic syndrome (MS). Background: Liver resections for HCC on MS are associated with high perioperative morbidity and mortality. No data on the minimally invasive approach in this setting exist. Material and Methods: A multicenter study involving 24 institutions was conducted. Propensity scores were calculated, and inverse probability weighting was used to weight comparisons. Short-term and long-term outcomes were investigated. Results: A total of 996 patients were included: 580 in OLR and 416 in MILR. After weighing, groups were well matched. Blood loss was similar between groups (OLR 275.9±3.1 vs MILR 226±4.0, P=0.146). There were no significant differences in 90-day morbidity (38.9% vs 31.9% OLRs and MILRs, P=0.08) and mortality (2.4% vs 2.2% OLRs and MILRs, P=0.84). MILRs were associated with lower rates of major complications (9.3% vs 15.3%, P=0.015), posthepatectomy liver failure (0.6% vs 4.3%, P=0.008), and bile leaks (2.2% vs 6.4%, P=0.003); ascites was significantly lower at postoperative day 1 (2.7% vs 8.1%, P=0.002) and day 3 (3.1% vs 11.4%, P<0.001); hospital stay was significantly shorter (5.8±1.9 vs 7.5±1.7, P<0.001). There was no significant difference in overall survival and disease-free survival. Conclusions: MILR for HCC on MS is associated with equivalent perioperative and oncological outcomes to OLRs. Fewer major complications, posthepatectomy liver failures, ascites, and bile leaks can be obtained, with a shorter hospital stay. The combination of lower short-term severe morbidity and equivalent oncologic outcomes favor MILR for MS when feasible.

Background and Objectives: Laparoscopic cholecystectomy (LC) is one of the most performed surgeries worldwide. Procedure difficulty and patient outcomes depend on several factors which are not considered in the current literature, including the learning curve, generating confusing and subjective results. This study aims to create a scoring system to calculate the learning curve of LC based on hepatobiliopancreatic (HPB) experts’ opinions during an educational course. Materials and Methods: A questionnaire was submitted to the panel of experts attending the HPB course at Research Institute against Digestive Cancer-IRCAD (Strasbourg, France) from 27–29 October 2022. Experts scored the proposed variables according to their degree of importance in the learning curve using a Likert scale from 1 (not useful) to 5 (very useful). Variables were included in the composite scoring system only if more than 75% of experts ranked its relevance in the learning curve assessment ≥4. A positive or negative value was assigned to each variable based on its effect on the learning curve. Results: Fifteen experts from six different countries attended the IRCAD HPB course and filled out the questionnaire. Ten variables were finally included in the learning curve scoring system (i.e., patient body weight/BMI, patient previous open surgery, emergency setting, increased inflammatory levels, presence of anatomical bile duct variation(s), and appropriate critical view of safety (CVS) identification), which were all assigned positive values. Minor or major intraoperative injuries to the biliary tract, development of postoperative complications related to biliary injuries, and mortality were assigned negative values. Conclusions: This is the first scoring system on the learning curve of LC based on variables selected through the experts’ opinions. Although the score needs to be validated through future studies, it could be a useful tool to assess its efficacy within educational programs and surgical courses.

Background: Metabolic syndrome (MS) is rapidly growing as risk factor for HCC. Liver resection for HCC in patients with MS is associated with increased postoperative risks. There are no data on factors associated with postoperative complications. Aims: The aim was to identify risk factors and develop and validate a model for postoperative major morbidity after liver resection for HCC in patients with MS, using a large multicentric Western cohort. Materials and Methods: The univariable logistic regression analysis was applied to select predictive factors for 90 days major morbidity. The model was built on the multivariable regression and presented as a nomogram. Performance was evaluated by internal validation through the bootstrap method. The predictive discrimination was assessed through the concordance index. Results: A total of 1087 patients were gathered from 24 centers between 2001 and 2021. Four hundred and eighty-four patients (45.2%) were obese. Most liver resections were performed using an open approach (59.1%), and 743 (68.3%) underwent minor hepatectomies. Three hundred and seventy-six patients (34.6%) developed postoperative complications, with 13.8% major morbidity and 2.9% mortality rates. Seven hundred and thirteen patients had complete data and were included in the prediction model. The model identified obesity, diabetes, ischemic heart disease, portal hypertension, open approach, major hepatectomy, and changes in the nontumoral parenchyma as risk factors for major morbidity. The model demonstrated an AUC of 72.8% (95% CI: 67.2%–78.2%) (https://childb.shinyapps.io/NomogramMajorMorbidity90days/). Conclusions: Patients undergoing liver resection for HCC and MS are at high risk of postoperative major complications and death. Careful patient selection, considering baseline characteristics, liver function, and type of surgery, is key to achieving optimal outcomes.