Dong, Yawen

Portal hypertension is a key factor in posthepatectomy liver failure (PHLF). While preoperative liver function tests like APRI+ALBI assess liver function, they only partially reflect portal hypertension severity. Elevated von Willebrand factor antigen (vWF-Ag) indicates endothelial dysregulation and correlates with portal hypertension. Combining vWF-Ag with APRI+ALBI may enhance PHLF prediction. A total of 534 patients who underwent liver resection at Mayo Clinic Rochester (2020–2024) were analyzed for PHLF incidence, postoperative morbidity, and 90-day mortality. Predictive probability for PHLF was assessed using receiver operating characteristic analysis and validated in an external Austrian cohort of 283 patients (2008–2017). vWF-Ag was then integrated into the existing APRI+ALBI multivariable model. PHLF grade B/C was reported in 56 patients (10.5%). The 90-day mortality rate was 0.9% (n=5). Using 2 cutoffs (182%, 240%), vWF-Ag was found to be an independent predictive factor for PHLF grade B/C that remained statistically significant upon multivariable analysis. The combination of preoperative APRI+ALBI and vWF-Ag increased the positive predictive value to 27.9% for PHLF grade B/C in the APRI+ALBI high and vWF-Ag high group. Incorporation of vWF-Ag into the established APRI+ALBI-based multivariable model revealed a superior AUC of 0.772 for PHLF risk stratification and was successfully validated in an independent cohort (AUC=0.834). The combination of vWF-Ag with APRI+ALBI demonstrates a favorable predictive potential for PHLF risk assessment. We provide 2 pathways for clinical assessment: (1) a cutoff-based system and (2) a more complex multivariable model that can be calculated in a specifically designed smartphone application.

Objective: To establish benchmark cutoffs for robotic liver resection (R-LR), encompassing both major and minor resections, and to determine the impact of patient selection on outcomes. Background: R-LR is a key advancement in minimally invasive liver surgery but lacks standardized benchmarks, especially for minor resections. While guidelines endorse R-LR, its role in optimizing outcomes remains unclear. This study establishes the first benchmarks for R-LR, enabling comparisons across surgical modalities and refining patient selection. Methods: This retrospective, multicenter study analyzed consecutive adult patients undergoing R-LR at 30 international centers (2020–2023). Benchmark centers had an annual case volume of ≥15 R-LR. Benchmark criteria included ASA ≤2, no major comorbidities, no prior liver resections, and Child-Pugh A status. Benchmark cutoffs for 14 key outcomes were set at the 50th and 75th percentiles of median values across benchmark centers. Multivariable logistic regression identified predictors of textbook outcomes. Results: Eighteen high-volume centers contributed 4028 cases with 2632 (65.3%) meeting benchmark criteria. Malignancy was the indication in 29.6%, most commonly hepatocellular carcinoma followed by colorectal liver metastases. Major liver resection was performed in 42.6%. The distribution of Iwate difficulty scores was low (25.4%), intermediate (53.9%), advanced (15.9%), and expert (4.9%). Benchmark cutoffs were established for minor and major resection, and stratified by Iwate low (0-3), intermediate (4-6) and high (7-12): Open conversion (≤6.5% minor, ≤10.5% major), major complications within 90 days (≤5.2% minor, ≤16.7% major), R1 resection (≤9.2% minor, ≤6.7% major). Benchmark cases performed at low-volume centers were able to achieve outcomes within the corresponding benchmark cutoffs. In fact, patient selection reflected by the proportion of benchmark patients, rather than case volume, was associated with textbook outcomes. Conclusions: This study defines R-LR benchmarks, emphasizing patient selection over center volume for optimal outcomes. Benchmark cutoffs guide training and support the expansion of R-LR.

Objective and Background: Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an aspartate aminotransferase to platelet ratio combined with an albumin-bilirubin grade (APRI+ALBI), based multivariable model (MVM) to predict PHLF and compare its performance to indocyanine green clearance (ICG-R15 or ICG-PDR) and albumin-ICG evaluation (ALICE). Methods: A total of 12,056 patients from the National Surgical Quality Improvement Program database were used to generate a MVM to predict PHLF B+C. The model was determined using stepwise backwards elimination. The performance of the model was tested using receiver operating characteristic curve analysis and validated in an international cohort of 2525 patients. In 620 patients, the APRI+ALBI MVM, trained in the National Surgical Quality Improvement Program cohort, was compared with the MVM’s based on other liver function tests (ICG clearance, ALICE) by comparing the areas under the curve (AUC). Results: A MVM including APRI+ALBI, age, sex, tumor type, and extent of resection was found to predict PHLF B+C with an AUC of 0.77, with comparable performance in the validation cohort (AUC: 0.74). In direct comparison with other MVM’s based on more expensive and time-consuming liver function tests (ICG clearance, ALICE), the APRI+ALBI MVM demonstrated equal predictive potential for PHLF B+C. A smartphone application for the calculation of the APRI+ALBI MVM was designed. Conclusion: Risk assessment through the APRI+ALBI MVM for PHLF B+C increases preoperative predictive accuracy and represents a universally available and cost-effective risk assessment before hepatectomy, facilitated by a freely available smartphone app.