Improving early cholecystectomy rate in acute cholecystitis with an evidence-based local multidisciplinary protocol and a surgical audit: single-center experience through an Acute Care Surgery Division.

PURPOSE: To analyze if, after implementation of an evidence-based local multidisciplinary protocol for acute cholecystitis (AC), an intermediate surgical audit could improve early cholecystectomy (EC) rate and other therapeutic indicators. METHODS: Longitudinal cohort study at a tertiary center. The local protocol, promoted, created, and periodically revised by the Acute Care Surgery Unit (ACSu) was updated and approved on March 2019. A specific registry was prospectively fulfilled with demographics, comorbidity, type of presentation, diagnostic items, therapeutic decision, and clinical course, considering both non-operative management (NOM) or cholecystectomy, early and delayed (EC and DC). Phase 1: April 2019-April 2021. A critical analysis and a surgical audit with the participation of all the involved Departments were then performed, especially focusing on improving global EC rate, considered primary outcome. Phase 2: May 2021-May 2023. Software SPSS 23.0 was used to compare data between phases. RESULTS: Initial EC rate was significantly higher on Phase 2 (39.3%vs52.5%, p < 0.004), as a significantly inferior rate of patients were initially bailed out from EC to NOM because of comorbidity (14.4%vs8%, p < 0.02) and grade II with severe inflammatory signs (7%vs3%, p < 0.04). A higher percentage of patients was recovered for EC after an initial decision of NOM on Phase 2, but without reaching statistical significance (21.8%vs29.2%, n.s.). Global EC rate significantly increased between phases (52.5%vs66.3%, p < 0.002) without increasing morbidity and mortality. A significant minor percentage of elective cholecystectomies after AC episodes had to be performed on Phase 2 (14%vs6.7%, p < 0.009). Complex EC and those indicated after readmission or NOM failure were usually performed by the ACSu staff. CONCLUSION: To adequately follow up the implementation of a local protocol for AC healthcare, registering and periodically analyzing data allow to perform intermediate surgical audits, useful to improve therapeutic indicators, especially EC rate. AC constitutes an ideal model to work with an ACSu.

Comparison of 3 Explant-Based Prognostic Models as Predictors of Hepatocellular Carcinoma Recurrence After Liver Transplantation: Analysis of Our Experience.

Tumor load is often underdiagnosed on radiological examination previous to liver transplantation (LT) for hepatocarcinoma (CHC). Thus, post-liver transplant explant analysis is required following transplantation to assess the risk of the recurrence of CHC. The objectives were to compare the characteristics of CHC on pre-LT radiological examination and explant histology and validate three models for the prediction of recurrence based on data from a cohort of patients treated in our hospital. METHODS: A retrospective study was undertaken of 105 LTs for CHC performed in our unit between January 2006 and January 2015. The minimum follow-up was five years. The preoperative radiological tumor stage was compared to the explant-based histologic stage. Three prognostic models were validated using our cohort of patients. RESULTS: Following Milan's criteria, the tumor load was underdiagnosed on pre-LT radiological examination in 20 patients, which accounted for 19% of the total sample. The 5-year overall recurrence was 6.6% for scores <4 and 33.3% for scores ≥4 according to Decaens' model; 7% for scores ≤7 and 25% for scores >7 in the Up-to-Seven model; and 3.6% for PCRS ≤0, 27.8% for PCRS1-2, and 100% for PCRS≥3 according to Chan's model. The predictive model for 5-year recurrence after LT with the greatest area under the curve was Chan's model (0.813 [95% CI: 0.650-0.977]) versus Decaens' model (0.674 [95% CI: 0.483-0.866]) and the Up-to-Seven model (0.481 [95% CI: 0.296-0.667]). CONCLUSIONS: A pre-LT radiological examination leads to the underdiagnosis of tumor load, and the risk for recurrence must be recalculated following LT. In light of the results obtained, Chan's model is more accurate in predicting 5-year recurrence of CHC post-LT based on 3 levels of risk. New prognostic models are needed to optimize the prediction of recurrence after liver transplantation for hepatocarcinoma.