Preoperative risk factors for massive transfusion, prolonged ventilation requirements, and mortality in patients undergoing liver transplantation

Preoperative fibrinogen level and blood transfusions in liver transplantation: A systematic review

BACKGROUND

Orthotopic liver transplantation (OLT) is a major surgery often associated with significant bleeding. We conducted a systematic review to explore the association between preoperative fibrinogen level and intraoperative blood products transfusion, blood loss and clinical outcomes in patients undergoing OLT.

METHODS

We included observational studies conducted in patients undergoing an OLT mostly for end-stage liver disease that reported an association between the preoperative fibrinogen level and our outcomes of interest. Our primary outcome was the intraoperative red blood cell (RBC) transfusion requirements. Our secondary outcomes were intraoperative blood loss, intraoperative transfusion of any blood product, postoperative RBC transfusion, postoperative thrombotic or hemorrhagic complications, and mortality. We used a standardized search strategy. We reported our results mostly descriptively but conducted meta-analyses using random-effect models when judged feasible.

RESULTS

We selected 24 cohort studies reporting at least one of our outcomes. We found that a high preoperative fibrinogen level was associated with fewer intraoperative RBC and other blood products transfusions, and lower blood loss. We also found a lower overall survival in patients with a higher fibrinogen level (pooled hazard ratio [95% CI] of 1.50 [1.23 to 1.84]; 5 studies, n = 1012, I2 = 48%). Only one study formally explored a fibrinogen level threshold effect. Overall, reporting was heterogeneous, and risk of bias was variable mostly because of uncontrolled confounding.

CONCLUSION

A higher preoperative fibrinogen level was associated with fewer intraoperative RBC and other blood products transfusions, lower blood loss, and higher mortality. Further studies may help clarify observed associations and inform guidelines.

Preoperative Fibrinogen Level and Bleeding in Liver Transplantation for End-stage Liver Disease: A Cohort Study

BACKGROUND

Liver transplantation is a high-risk surgery associated with important perioperative bleeding and transfusion needs. Uncertainties remain on the association between preoperative fibrinogen level and bleeding in this population.

METHODS

We conducted a cohort study that included all consecutive adult patients undergoing a liver transplantation for end-stage liver disease in 1 center. We analyzed the association between the preoperative fibrinogen level and bleeding-related outcomes. Our primary outcome was intraoperative blood loss, and our secondary outcomes were estimated perioperative blood loss, intraoperative and perioperative red blood cell transfusions, reinterventions for bleeding and 1-y graft and patient survival. We estimated linear regression models and marginal risk models adjusted for all important potential confounders. We used restricted cubic splines to explore potential nonlinear associations and reported dose-response curves.

RESULTS

We included 613 patients. We observed that a lower fibrinogen level was associated with a higher intraoperative blood loss, a higher estimated perioperative blood loss and a higher risk of intraoperative and perioperative red blood cell transfusions (nonlinear effects). Based on an exploratory analysis of the dose-response curves, these effects were observed below a threshold value of 3 g/L for these outcomes. We did not observe any association between preoperative fibrinogen level and reinterventions, 1-y graft survival or 1-y patient survival.

CONCLUSIONS

This study suggests that a lower fibrinogen level is associated with bleeding in liver transplantation. The present results may help improving the selection of patients for further studies on preoperative fibrinogen administration in liver transplant recipients with end-stage liver disease.

Development and Validation of a Prediction Model for Need for Massive Transfusion During Surgery Using Intraoperative Hemodynamic Monitoring Data

Importance

Massive transfusion is essential to prevent complications during uncontrolled intraoperative hemorrhage. As massive transfusion requires time for blood product preparation and additional medical personnel for a team-based approach, early prediction of massive transfusion is crucial for appropriate management.

Objective

To evaluate a real-time prediction model for massive transfusion during surgery based on the incorporation of preoperative data and intraoperative hemodynamic monitoring data.

Design, Setting, and Participants

This prognostic study used data sets from patients who underwent surgery with invasive blood pressure monitoring at Seoul National University Hospital (SNUH) from 2016 to 2019 and Boramae Medical Center (BMC) from 2020 to 2021. SNUH represented the development and internal validation data sets (n = 17 986 patients), and BMC represented the external validation data sets (n = 494 patients). Data were analyzed from November 2020 to December 2021.

Exposures

A deep learning-based real-time prediction model for massive transfusion.

Main Outcomes and Measures

Massive transfusion was defined as a transfusion of 3 or more units of red blood cells over an hour. A preoperative prediction model for massive transfusion was developed using preoperative variables. Subsequently, a real-time prediction model using preoperative and intraoperative parameters was constructed to predict massive transfusion 10 minutes in advance. A prediction model, the massive transfusion index, calculated the risk of massive transfusion in real time.

Results

Among 17 986 patients at SNUH (mean [SD] age, 58.65 [14.81] years; 9036 [50.2%] female), 416 patients (2.3%) underwent massive transfusion during the operation (mean [SD] duration of operation, 170.99 [105.03] minutes). The real-time prediction model constructed with the use of preoperative and intraoperative parameters significantly outperformed the preoperative prediction model (area under the receiver characteristic curve [AUROC], 0.972; 95% CI, 0.968-0.976 vs AUROC, 0.824; 95% CI, 0.813-0.834 in the SNUH internal validation data set; P < .001). Patients with the highest massive transfusion index (ie, >90th percentile) had a 47.5-fold increased risk for a massive transfusion compared with those with a lower massive transfusion index (ie, <80th percentile). The real-time prediction model also showed excellent performance in the external validation data set (AUROC of 0.943 [95% CI, 0.919-0.961] in BMC).

Conclusions and Relevance

The findings of this prognostic study suggest that the real-time prediction model for massive transfusion showed high accuracy of prediction performance, enabling early intervention for high-risk patients. It suggests strong confidence in artificial intelligence-assisted clinical decision support systems in the operating field.

The fundamentals of sex-based disparity in liver transplantation: Understanding can lead to change

Liver transplantation (LT) is the definitive treatment for end-stage liver disease. Unfortunately, women are disadvantaged at every stage of the LT process. We conducted a literature review to increase the understanding of this disparity. Hormonal differences, psychological factors, and Model for End-Stage Liver Disease (MELD) score inequalities are some pretransplantation factors that contribute to this disparity. In the posttransplantation setting, women have differing risk than men in most major outcomes (perioperative complications, rejection, long-term renal dysfunction, and malignancy) and assessing the two groups together is disadvantageous. Herein, we propose interventions including standardized criteria for LT referral, using an alternate MELD, education for support of women, and motivating women to seek living donors. Understanding sex-based differences will allow us to improve access, tailor management, and improve overall outcomes for all patients, particularly women.

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who had undergone liver transplantation. These data included emergency information, donor information, demographic data, preoperative laboratory data, the etiology of hepatic failure, the Model for End-stage Liver Disease (MELD) score, surgical history, antiplatelet therapy, continuous renal replacement therapy (CRRT), the preoperative dose of vasopressor, and the estimated blood loss (EBL) during surgery. The logistic regression model was one of the best-performing machine learning models. The most important factors for the prediction of massive hemorrhage were the disease etiology, activated partial thromboplastin time (aPTT), operation duration, body temperature, MELD score, mean arterial pressure, serum creatinine, and pulse pressure. The risk-scoring system was developed using the odds ratios of these factors from the logistic model. The risk-scoring system showed good prediction performance and calibration (AUROC: 0.775, AUPR: 0.753).

Perioperative management of adult living donor liver transplantation: Part 1 - recipients

Living donor liver transplantation was first developed to mitigate the limited access to deceased donor organs in Asia in the 1990s. This alternative liver transplantation option has become an established and widely practiced transplantation method for adult patients suffering from end-stage liver disease. It has successfully addressed the shortage of deceased donors. The Society for the Advancement of Transplant Anesthesia and the Korean Society of Transplant Anesthesia jointly reviewed published studies on the perioperative management of live donor liver transplant recipients. The review aims to offer transplant anesthesiologists and critical care physicians a comprehensive overview of the perioperative management of adult live liver transplantation recipients. We feature the status, outcomes, surgical procedure, portal venous decompression, anesthetic management, prevention of acute kidney injury, avoidance of blood transfusion, monitoring and therapeutic strategies of hemodynamic derangements, and Enhanced Recovery After Surgery protocols for liver transplant recipients. This article is protected by copyright. All rights reserved.

Advancing Prediction of Risk of Intraoperative Massive Blood Transfusion in Liver Transplantation With Machine Learning Models. A Multicenter Retrospective Study

Background

Liver transplantation surgery is often accompanied by massive blood loss and massive transfusion (MT), while MT can cause many serious complications related to high mortality. Therefore, there is an urgent need for a model that can predict the demand for MT to reduce the waste of blood resources and improve the prognosis of patients.

Objective

To develop a model for predicting intraoperative massive blood transfusion in liver transplantation surgery based on machine learning algorithms.

Methods

A total of 1,239 patients who underwent liver transplantation surgery in three large grade lll-A general hospitals of China from March 2014 to November 2021 were included and analyzed. A total of 1193 cases were randomly divided into the training set (70%) and test set (30%), and 46 cases were prospectively collected as a validation set. The outcome of this study was an intraoperative massive blood transfusion. A total of 27 candidate risk factors were collected, and recursive feature elimination (RFE) was used to select key features based on the Categorical Boosting (CatBoost) model. A total of ten machine learning models were built, among which the three best performing models and the traditional logistic regression (LR) method were prospectively verified in the validation set. The Area Under the Receiver Operating Characteristic Curve (AUROC) was used for model performance evaluation. The Shapley additive explanation value was applied to explain the complex ensemble learning models.

Results

Fifteen key variables were screened out, including age, weight, hemoglobin, platelets, white blood cells count, activated partial thromboplastin time, prothrombin time, thrombin time, direct bilirubin, aspartate aminotransferase, total protein, albumin, globulin, creatinine, urea. Among all algorithms, the predictive performance of the CatBoost model (AUROC: 0.810) was the best. In the prospective validation cohort, LR performed far less well than other algorithms.

Conclusion

A prediction model for massive blood transfusion in liver transplantation surgery was successfully established based on the CatBoost algorithm, and a certain degree of generalization verification is carried out in the validation set. The model may be superior to the traditional LR model and other algorithms, and it can more accurately predict the risk of massive blood transfusions and guide clinical decision-making.

Transparency considerations for describing statistical analyses in research

Researchers who use the results of statistical analyses to draw conclusions about collected data must write a statistical analysis section in their manuscript. Describing statistical analyses in precise detail is as important as presenting the dosages of drugs and methodology of interventions. It is also essential for scientific accuracy and transparency in scientific research. We evaluated the quality of the statistical analysis sections of clinical research articles published in the Korean Journal of Anesthesiology between February 2020 and February 2021. Using a Likert scale where 1, 2, and 3 represented “not described at all,” “partially described,” and “fully described,” respectively, the following 6 items were assessed: 1) stating of the statistical analysis methods used, 2) rationale for and detailed description of the statistical analysis methods used, 3) parameters derived from the statistical analyses, 4) type and version of the statistical software package used, 5) significance level, and 6) sidedness of the test (one-sided vs. two-sided). The first 3 items evaluate issues directly related to the statistical analysis methods used and last 3 are indirectly related items. In all the included articles, the statistical analysis methods used were stated (score of 3). However, only 4 articles (12.9%) fully described the sidedness of the test (score of 3). Authors tend not to describe the sidedness of statistical analysis tests in the methodology section of clinical research articles. It is essential that the sidedness be described in research studies.

The Impact of Intraoperative Donor Blood on Packed Red Blood Cell Transfusion During Deceased Donor Liver Transplantation: A Retrospective Cohort Study

BACKGROUND

Blood from deceased organ donors, also known as donor blood (DB), has the potential to reduce the need for packed red blood cells (PRBCs) during liver transplantation (LT). We hypothesized that DB removed during organ procurement is a viable resource that could reduce the need for PRBCs during LT.

METHODS

We retrospectively examined data on LT recipients aged over 18 y who underwent a deceased donor LT. The primary aim was to compare the incidence of PRBC transfusion in LT patients who received intraoperative DB (the DB group) to those who did not (the nondonor blood [NDB] group).

RESULTS

After a propensity score matching process, 175 patients received DB and 175 did not. The median (first-third quartile) volume of DB transfused was 690.0 mL (500.0-900.0), equivalent to a median of 3.1 units (2.3-4.1). More patients in the NDB group received an intraoperative PRBC transfusion than in the DB group: 74.3% (95% confidence intervals, 67.8-80.8) compared with 60% (95% confidence intervals, 52.7-67.3); P = 0.004. The median number of PRBCs transfused intraoperatively was higher in the NDB group compared with the DB group: 3 units (0-6) compared with 2 units (0-4); P = 0.004. There were no significant differences observed in the secondary outcomes.

CONCLUSIONS

Use of DB removed during organ procurement and reinfused to the recipient is a viable resource for reducing the requirements for PRBCs during LT. Use of DB minimizes the exposure of the recipient to multiple donor sources.

Impact of Perioperative Massive Transfusion on Long Term Outcomes of Liver Transplantation: a Retrospective Cohort Study

Background: Liver transplantation (LT) is associated with a significant risk of intraoperative hemorrhage and massive blood transfusion. However, there are few relevant reports addressing the long-term impacts of massive transfusion (MT) on liver transplantation recipients. Aim: To assess the effects of MT on the short and long-term outcomes of adult liver transplantation recipients. Methods: We included adult patients who underwent liver transplantation at West China Hospital from January 2011 to February 2015. MT was defined as red blood cell (RBC) transfusion of ≥10 units within 48 hours since the application of LT. Preoperative, intraoperative and postoperative information were collected for data analyzing. We used one-to-one propensity-matching to create pairs. Kaplan-Meier survival analysis was used to compare long-term outcomes of LT recipients between the MT and non-MT groups. Univariate and multivariate logistic regression analyses were performed to evaluate the risk factors associated with MT in LT. Results: Finally, a total of 227 patients were included in our study. After propensity score matching, 59 patients were categorized into the MT and 59 patients in non-MT groups. Compared with the non-MT group, the MT group had a higher 30-day mortality (15.3% vs 0, p=0.006), and a higher incidence of postoperative complications, including postoperative pulmonary infection, abdominal hemorrhage, pleural effusion and severe acute kidney injury. Furthermore, MT group had prolonged postoperative ventilation support (42 vs 25 h, p=0.007) and prolonged durations of ICU (12.9 vs 9.5 d, p<0.001) stay. Multivariate COX regression indicated that massive transfusion (OR: 2.393, 95% CI: 1.164-4.923, p=0.018) and acute rejection (OR: 7.295, 95% CI: 2.108-25.246, p=0.02) were significant risk factors affecting long-term survivals of LT patients. The 1-year and 3-year survival rates patients in MT group were 82.5% and 67.3%, respectively, while those of non-MT group were 93.9% and 90.5%, respectively. The MT group exhibited a lower long-term survival rate than the non-MT group (HR: 2.393, 95% CI: 1.164-4.923, p<0.001). Finally, the multivariate logistic regression revealed that preoperative hemoglobin <118 g/L (OR: 5.062, 95% CI: 2.292-11.181, p<0.001) and intraoperative blood loss ≥1100 ml (OR: 3.212, 95% CI: 1.586-6.506, p = 0.001) were the independent risk factor of MT in patients undergoing LT. Conclusion: Patients receiving MT in perioperative periods of LT had worse short-term and long-term outcomes than the non-MT patients. Massive transfusion and acute rejection were significant risk factors affecting long-term survivals of LT patients, and intraoperative blood loss of over 1100 ml was the independent risk factor of MT in patients undergoing LT. The results may offer valuable information on perioperative management in LT recipients who experience high risk of MT.

Risk Factors for Hepatocellular Carcinoma Recurrence and Survival after Liver Transplantation in Patients with HCV-Related Cirrhosis

Purpose

We aimed to identify prognostic factors for survival and recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) for patients with HCC and hepatitis C virus-related cirrhosis (HCV-cirrhosis).

Methods

This retrospective cohort study followed all adult patients with HCV-cirrhosis who underwent LT because of HCC or had incidental HCC identified through pathologic examination of the explanted liver at a university hospital in Rio de Janeiro, Brazil, over 11 years (1998-2008). We used Cox regression models to assess the following risk factors regarding HCC recurrence or death after LT: age, Model for End-stage Liver Disease score, Child-Pugh classification, alpha-fetoprotein (AFP), whether patients had undergone locoregional treatment before transplantation, the number of packed red blood cell units (PRBCU) transfused during surgery, the number and size of HCC lesions in the explanted liver, and the presence of microvascular invasion and necrotic areas within HCC lesions.

Results

Seventy-six patients were followed up for a median (interquartile range (IQR)) of 4.4 (0.7-6.6) years. Thirteen (17%) patients had HCC recurrence during the follow-up period, and 26 (34%) died. The median survival time was 6.6 years (95% CI: 2.4-12.0), and the 5-year survival was 52.5% (95% CI: 42.3-65.0%). The final regression model for overall survival included four variables: age (hazard ratio (HR): 1.02, 95% CI: 0.96-1.08, P = 0.603), transplantation waiting time (HR: 1.00, 95% CI: 1.00-1.00, P = 0.190), preoperative AFP serum levels (HR: 1.01, 95% CI: 1.00-1.02, P = 0.006), and whether >4 PRBCU were transfused during surgery (HR: 1.15, 95% CI: 1.05-1.25, P = 0.001). The final cause-specific Cox regression model for HCC recurrence included only microvascular invasion (HR: 14.86, 95% CI: 4.47-49.39, P < 0.001).

Conclusion

In this study of LT for HCV-cirrhosis, preoperative AFP levels and the number of PRBCU transfused during surgery were associated with overall survival, whereas microvascular invasion with HCC recurrence.