Factors Associated with Prolonged Recipient Hepatectomy Time During Liver Transplantation: A Single-Centre Experience

Cold ischemia time in liver transplantation: An overview

The standard approach to organ preservation in liver transplantation is by static cold storage and the time between the cross-clamping of a graft in a donor and its reperfusion in the recipient is defined as cold ischemia time (CIT). This simple definition reveals a multifactorial time frame that depends on donor hepatectomy time, transit time, and recipient surgery time, and is one of the most important donor-related risk factors which may influence the graft and recipient's survival. Recently, the growing demand for the use of marginal liver grafts has prompted scientific exploration to analyze ischemia time factors and develop different organ preservation strategies. This review details the CIT definition and analyzes its different factors. It also explores the most recent strategies developed to implement each timestamp of CIT and to protect the graft from ischemic injury.

Perceptions of surgical difficulty in liver transplantation: A European survey and development of the Pitié-Salpêtrière classification

BACKGROUND

Significant variations exist regarding the definition of difficult liver transplantation. The study goals were to investigate how liver transplant surgeons evaluate the surgical difficulty of liver transplantation and to use the identified factors to classify liver transplantation difficulty.

METHODS

A Web-based online European survey was presented to liver transplant surgeons. The survey was divided into 3 parts: (1) participant demographics and practices; (2) various situations based on recipient, liver disease, tumor treatment, and technical factors; and (3) 8 real-life clinical vignettes with different levels of complexity. In part 3 of the survey, respondents were asked whether they would perform liver transplantation but were not aware that these patients eventually underwent liver transplantation.

RESULTS

A total of 143 invites were sent out, and 97 (67.8%) participants completed the survey. Most participants considered previous spontaneous bacterial peritonitis, previous supra-mesocolic surgery, hypertrophy of segment I, and obesity to be recipient factors for high-difficulty liver transplantation. Most participants considered liver transplantation to be challenging in patients with Budd-Chiari syndrome, Kasai surgery, polycystic liver disease, diffuse portal vein thrombosis, and a history of open hepatectomy. The proportion of participants indicating that liver transplantation was warranted varied across the 8 cases, from 69% to 100%. Our classification of the surgical difficulty of liver transplantation employed these recipient-related, surgical history-related, and liver disease-related variables and 3 difficulty groups were identified: low, intermediate, and high difficulty groups.

CONCLUSION

This survey provides an overview of the surgical difficulty of various situations in liver transplantation that could be useful for further benchmark and textbook outcome studies.

Development of a preoperative score to predict surgical difficulty in liver transplantation

BACKGROUND

A difficulty score to predict intraoperative surgical complexity in liver transplantation has never been developed. The aim of this study was to assess factors associated with a difficult liver transplant and develop a score to predict difficult surgery.

METHODS

All patients undergoing deceased donor whole liver transplantation from 2012 to 2019 at a single center were included. Estimated intraoperative blood loss (mL/kg) and surgery duration (skin-to-arterial reperfusion time) were used as surrogates of difficulty. Based on these variables, the study population was divided into 2 groups: high risk and standard risk of difficulty. Univariate and multivariate analyses were performed to identify predictors associated with a demanding liver transplantation and develop a difficulty score.

RESULTS

A total of 515 patients were included in the study population, and 101 (20%) were considered difficult operations. Patients with a higher risk of difficulty showed a significantly higher rate of Clavien-Dindo ≥III complications (50.5% vs 24.4%, P = .001) and a longer hospital stay (19 vs 16 days, P = .001). Preoperative factors associated with difficulty were retransplantation (odds ratio 4.34, P = .001), preoperative portal vein thrombosis (odds ratio 3.419, P = .001), previous upper abdominal surgery (odds ratio 2.161, P = .003), spontaneous bacterial peritonitis (odds ratio 1.985, P < .02), and prior variceal bleeding (odds ratio 1.401, P = .051). A 10-point difficulty score was created, showing a negative predictive value of 84% at 4 points.

CONCLUSION

Difficult liver transplantation surgery, as assessed by skin-to-arterial reperfusion time and estimated blood loss, is associated with worse perioperative outcomes. We developed a simple score with clinical preoperative variables that predicts difficult surgery, and therefore, it may help to optimize allocation policies and perioperative logistics.

Liver Transplantation for Biliary Atresia in Adulthood: Single-Centre Surgical Experience

Background: Biliary atresia (BA) is the most common indicator for liver transplant (LT) in children, however, approximately 22% will reach adulthood with their native liver, and of these, half will require transplantation later in life. The aim of this study was to analyse the surgical challenges and outcomes of patients with BA undergoing LT in adulthood. Methods: Patients with BA requiring LT at the age of 16 or older in our unit between 1989 and 2020 were included. Pretransplant, perioperative variables and outcomes were analysed. Pretransplant imaging was reviewed to assess liver appearance, spontaneous visceral portosystemic shunting (SPSS), splenomegaly, splenic artery (SA) size, and aneurysms. Results: Thirty-four patients who underwent LT for BA fulfilled the inclusion criteria, at a median age of 24 years. The main indicators for LT were synthetic failure and recurrent cholangitis. In total, 57.6% had significant enlargement of the SA, 21% had multiple SA aneurysm, and SPSS was present in 72.7% of the patients. Graft and patient survival at 1, 5, and 10 years was 97.1%, 91.2%, 91.2% and 100%, 94%, 94%, respectively Conclusions: Good outcomes after LT for BA in young patients can be achieved with careful donor selection and surgery to minimise the risk of complications. Identification of anatomical variants and shunting are helpful in guiding attitude at the time of transplant.

The Impact of Time Interval between Hepatic Resection and Liver Transplantation on Clinical Outcome in Patients with Hepatocellular Carcinoma

Simple Summary

Recurrence of disease or worsening of liver function after hepatic resection (HR) for hepatocellular carcinoma (HCC) may require secondary liver transplantation (SLT). However, a history of HR is supposed to increase the surgical complexity of LT. This is one of the largest series of SLT and it demonstrates that among all the features analyzed regarding the prior HR, only time interval between HR and SLT was an independent predictor of severe complications after SLT. In particular, an increasing probability of severe complications was observed in those patients who were transplanted close (<15 months) to the HR. There was no significant association between HCC-related death and the time between HR and SLT at the multivariable competing risks regression model. Furthermore, these results remained inside the benchmark values recently reported for LT, confirming that tertiary referral centers with consistent experience in HPB surgery and LT may have benefits in both fields.

Abstract

Hepatic resection (HR) for hepatocellular carcinoma (HCC) may require secondary liver transplantation (SLT). However, a previous HR is supposed to worsen post-SLT outcomes. Data of patients treated by SLT between 2000 and 2018 at two tertiary referral centers were analyzed. The primary outcome of the study was to analyze the impact of HR on post-LT complications. A Comprehensive Complication Index ≥ 29.6 was chosen as cutoff. The secondary outcome was HCC-related death by means of competing-risk regression analysis. In the study period, 140 patients were included. Patients were transplanted in a median of 23 months after HR (IQR 14–41). Among all the features analyzed regarding the prior HR, only time interval between HR and SLT (time HR-SLT) was an independent predictor of severe complications after LT (OR = 0.98, p < 0.001). According to fractional polynomial regression, the probability of severe complications increased up to 15 months after HR (43%), then slowly decreased over time (OR = 0.88, p < 0.001). There was no significant association between HCC-related death and time HR-SLT at the multivariable competing risks regression model (SHR, 1.06; 95% CI: 0.69–1.62, p = 0.796). This study showed that time HR-SLT was key in predicting complications after LT, without affecting HCC-related death.

The learning curve for piggyback liver transplantation: identifying factors challenging surgery

BACKGROUND

This study aimed to quantify the learning curve of piggyback liver transplantation and to identify factors that impact the operative time and blood transfusion during the learning curve.

METHODS

A retrospective review was performed on consecutive cases of patients' first piggyback liver transplantations that were performed by a single surgeon. The learning curve for the operative time was evaluated using the cumulative sum method.

RESULTS

There were 181, consecutive, first-time piggyback liver transplantations. The median operative time was 345 minutes (range: 180-745 minutes) with a median transfusion rate of 4 packed red blood cell units (range: 0-23 units). The cumulative sum learning curve identified 3 phases: an initial phase (1-70 piggyback liver transplantations), a plateau phase (71-101 piggyback liver transplantations), and a stable phase (102-181 piggyback liver transplantations). Over the 3 phases, there were significant decreases in the median duration of the surgery (388.8 vs 344.8 vs 326.9 minutes; P = .004, P = .0004, P ≤ .0001) and the number of red blood cell units transfused (6.00 vs 3.90 vs 3.71; P = .02, P = .79, P = .0006). Multivariable analysis identified that the following factors impacted the operative time: surgeon experience (P = .00006), previous upper abdominal surgery (P = .01), portocaval shunt fashioning (P = .0003), early portal section (P = .00001), multiple arterial graft reconstruction (P = .03), and the length of the retrohepatic inferior vena covered by segment 1 (P = .0006). Independent risk factors for increased blood loss were surgeon experience (P = .0001), previous upper abdominal surgery (P = .002), the retrohepatic inferior vena cava encirclement by segment 1 (P = .0001), severe portal hypertension (P = .01), early portal section (P = .001), and low prothrombin time (P = .00001).

CONCLUSION

Easily identifiable factors related to recipients (segment 1 morphology, previous upper abdominal surgery, severe portal hypertension) and to surgeon (operative experience, portocaval shunt fashioning, early portal section, and multiple arterial reconstructions) impact operative time and blood loss during the learning curve of piggyback liver transplantation. These factors can be used for grading the difficulties of liver transplantation to tailor the surgical strategy.