Development and Validation of a Nomogram for Predicting Incidence of Early Allograft Dysfunction Following Liver Transplantation

Artificial intelligence for prediction of donor liver allograft steatosis and early post-transplantation graft failure

BACKGROUND

Donor livers undergo subjective pathologist review of steatosis before transplantation to mitigate the risk for early allograft dysfunction (EAD). We developed an objective, computer vision artificial intelligence (CVAI) platform to score donor liver steatosis and compared its capability for predicting EAD against pathologist steatosis scores.

METHODS

Two pathologists scored digitized donor liver biopsy slides from 2014 to 2019. We trained four CVAI platforms with 1:99 training:prediction split. Mean intersection-over-union (IU) characterized CVAI model accuracy. We defined EAD using liver function tests within 1 week of transplantation. We calculated separate EAD logistic regression models with CVAI and pathologist steatosis and compared the models' discrimination and internal calibration.

RESULTS

From 90 liver biopsies, 25,494 images trained CVAI models yielding peak mean IU = 0.80. CVAI steatosis scores were lower than pathologist scores (median 3% vs 20%, P < 0.001). Among 41 transplanted grafts, 46% developed EAD. The median CVAI steatosis score was higher for those with EAD (2.9% vs 1.9%, P = 0.02). CVAI steatosis was independently associated with EAD after adjusting for donor age, donor diabetes, and MELD score (aOR = 1.34, 95%CI = 1.03-1.75, P = 0.03).

CONCLUSION

The CVAI steatosis EAD model demonstrated slightly better calibration than pathologist steatosis, meriting further investigation into which modality most accurately and reliably predicts post-transplantation outcomes.

Uric Acid as a Predictor for Early Allograft Dysfunction after Living Donor Liver Transplantation: A Prospective Observational Study

Early allograft dysfunction (EAD) is a postoperative complication that may cause graft failure and mortality after liver transplantation. The objective of this study was to examine whether the preoperative serum uric acid (SUA) level may predict EAD. We performed a prospective observational study, including 61 donor/recipient pairs who underwent living donor liver transplantation (LDLT). In the univariate and multivariate analysis, SUA ≤4.4 mg/dL was related to a five-fold (odds ratio (OR): 5.16, 95% confidence interval (CI): 1.41–18.83; OR: 5.39, 95% CI: 1.29–22.49, respectively) increased risk for EAD. A lower preoperative SUA was related to a higher incidence of and risk for EAD. Our study provides a new predictor for evaluating EAD and may exert a protective effect against EAD development.

Severity of early allograft dysfunction following donation after circulatory death liver transplantation: a multicentre study

Background

Early allograft dysfunction (EAD) is associated with decreased graft and patient survival rates. This study aimed to identify the severity of EAD and develop a predictive model for EAD after donation after circulatory death (DCD) liver transplantation (LT). Furthermore, the influence of operative time on EAD incidence was also evaluated.

Methods

In this retrospective, multicentre cohort study, nomograms were established based on a single-centre training cohort (n=321) and validated in a 3-center validation cohort (n=501).

Results

The incidence rate of EAD was 46.4% (149/321) in the training cohort and 40.5% (203/501) in the validation cohort. Of the 149 EAD patients in the training cohort, 77 patients with either elevated alanine aminotransferase (ALT) or aspartate aminotransferase (AST) were classified as having EAD type A, and the rest of the EAD patients were classified as having EAD type B. Recipients with EAD type B had lower graft and patient survival rates than recipients with EAD type A (P=0.043 and 0.044, respectively). We further developed a nomogram to predict EAD (graft weight, cold ischemia time, donor age, model for end-stage liver disease (MELD) score) and another nomogram to predict EAD type B (graft weight, cold ischemia time, MELD score). The nomograms for the prediction of EAD and EAD type B had good discrimination [concordance index (C-index) =0.712 (0.666-0.758), 0.707 (0.641-0.773)] and calibration [Hosmer-Lemeshow (HL) P=0.384, P=0.425] in the validation cohort. An increased operative time (>6 h) was associated with increased EAD and EAD type B incidence in the high-risk group (P=0.005, P=0.020, respectively).

Conclusions

EAD type B was associated with decreased graft and patient survival rates. The novel nomograms effectively predicted the incidence of EAD and EAD type B in DCD LT patients.

A nomogram for prediction of early allograft dysfunction in living donor liver transplantation

Liver transplantation is the treatment of choice for end-stage liver diseases. However, early allograft dysfunction (EAD) is frequently encountered and associated with graft loss or mortality after transplantation. This study aimed to establish a predictive model of EAD after living donor liver transplantation. A total of 77 liver transplants were recruited to the study. Multivariate analysis was utilized to identify significant risk factors for EAD. A nomogram was constructed according to the contributions of the risk factors. The predictive values were determined by discrimination and calibration methods. A cohort of 30 patients was recruited to validate this predictive model. Four independent risk factors, including donor age, intraoperative blood loss, preoperative alanine aminotransferase (ALT), and reperfusion total bilirubin, were identified and used to build the nomogram. The c-statistics of the primary cohort and the validation group were 0.846 and 0.767, respectively. The calibration curves for the probability of EAD presented an acceptable agreement between the prediction by the nomogram and the actual incidence. In conclusion, the study developed a new nomogram for predicting the risk of EAD following living donor liver transplantation. This model may help clinicians to determine individual risk of EAD following living donor liver transplantation.

First Preliminary Experience with Preservation of Liver Grafts from Extended-Criteria Donors by Normothermic Machine Perfusion in Asia

BACKGROUND Normothermic machine perfusion (NMP) can provide access to evaluate and resuscitate high-risk donor livers before transplantation. The purpose of this study was to determine the efficacy of NMP in preservation and assessment of extended-criteria donor (ECD) livers in China. CASE REPORT From September 2018 to March 2019, 4 liver grafts from 3 transplant center defined as ECD were subjected to NMP, and then were transplanted successfully. During perfusion, perfusion parameters such as vascular flow, glucose level, lactate clearance, and bile production/composition were recorded to assess graft viability. All recipients were followed up 6 months after transplantation. CONCLUSIONS NMP provides a potential tool for preservation and assessment of ECD livers in China.

A two-circular RNA signature of donor circFOXN2 and circNECTIN3 predicts early allograft dysfunction after liver transplantation

Background

Early allograft dysfunction (EAD) following liver transplantation is associated with poor recipient and graft survival. In recent years, circular RNAs (circRNAs) have emerged as important components of endogenous RNAs. This study aims to explore the expression profile and predictive value of graft circular RNAs for EAD after liver transplantation.

Methods

RNA sequencing was conducted to identify the circRNA profile in donor liver tissues. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was used to identify candidate circRNAs. A novel model combining circular RNA signature was established to predict EAD based on the multivariate analysis.

Results

A total of 442 circRNAs were differentially expressed between the EAD and non-EAD groups, of which, 223 were significantly upregulated and 219 were downregulated in the EAD group (Fold change >2, P<0.05). qRT-PCR validation indicated that circFOXN2 and circNECTIN3 levels in the EAD group were significantly lower than those in the non-EAD group (P=0.038, 0.024, respectively; n=115). Among the 115 recipients, 32 recipients with high circFOXN2 expression were classified as circular RNA signature A and the rest recipients with low circFOXN2 expression were categorized into circular RNA signature B (n=33, high circNECTIN3 expression) and C (n=50, low circNECTIN3 expression). The incidence rates of EAD in signature A, B and C were significantly different (3.1%, 21.2% and 42.0%, respectively; P=0.000). According to the multivariate analysis, a novel predictive model for EAD was developed based on CIT (P=0.000) and circular RNA signature (P=0.013). The novel model displayed a high predictive value for EAD with areas under the curve (AUC) of 0.870 (95% CI: 0.797-0.942).

Conclusions

Donor circFOXN2 and circNEXTIN3 were associated with the incidence of EAD. The novel model combing the two-circular RNA signature had a high predictive value for EAD.

The postoperative hepatic artery resistance index after living donor liver transplantation can predict early allograft dysfunction

To investigate whether postoperative hepatic hemodynamics have an impact on graft function.Using a retrospective cohort with 262 adult living donor liver transplantation (LDLT) recipients, we discussed the relationship between postoperative hepatic hemodynamics and patient outcomes.According to the definition of early allograft dysfunction (EAD), the patients were classified into the EAD group (43 patients) and the non-EAD group (219 patients). In terms of postoperative hemodynamic parameters, there was no significant differences between these 2 groups regarding hepatic artery flow (HAF), hepatic artery velocity (HAV), portal vein flow (PVF), and portal vein velocity (PVV), except for the hepatic artery resistance index (HARI) which was somewhat higher in the EAD group on postoperative day 3 (POD3) (0.70 vs 0.61, P < .05). According to these results, we used a ROC curve and found that a HARI of 0.68 was the cutoff point (with 73.8% sensitivity and 58.3% specificity) for predicting EAD after LDLT. In addition, multivariate analysis showed that fulminant hepatic failure, pretransplant hepatorenal syndrome, and HARI ≥ 0.68 on POD3 were independent risk factors for postoperative EAD.Our results showed that postoperative hemodynamics might influence graft function by altering hepatic artery flow.

Analysis of Data from the Oxygen Persufflation in Liver Transplantation (OPAL) Study to Determine the Role of Factors Affecting the Hepatic Microcirculation and Early Allograft Dysfunction

Background

Adequate microcirculatory perfusion is essential for the provision of oxygen to the liver following transplantation. Data from the Oxygen Persufflation in Liver Transplantation (OPAL) study (ISRCTN00167887) were analyzed from liver transplants performed at a single center to determine the role of factors affecting the hepatic microcirculation and early allograft dysfunction (EAD).

Material/Methods

Retrospective data from 116 patients from the Oxygen Persufflation as Adjunction in Liver Transplantation (OPAL) study who underwent liver transplantation at a single center were analyzed. Oxygen saturation of hemoglobin (SO₂), relative capillary hemoglobin concentration (rHb), relative tissue blood flow (rBF) using laser Doppler flow measurements, and the Oxygen-to-See (O2C) spectrometry were measured and with post-transplant allograft function were analyzed using univariate and multivariate logistic regression statistics.

Results

Livers donors had a median donor risk index of 1.8. Most liver transplant recipients were men (60.3%), with a median age of 54 years (IQR, 23–68 years). Mean post-transplant 3-month survival was 90.5%. The EAD rate was 22.4%, the median SO₂ was 78% (IQR, 29.5–95.8%), the median rHb was 55.6 AU (IQR, 16.8–74.8 AU), and the median rBF was 110.1 AU (IQR, 35.8–406.8 AU). Multivariate logistic regression analysis showed that tissue SO₂ (p=0.01), body mass index (BMI) of the transplant recipient (p=0.002), serum alanine transaminase (ALT) of the donor (p=0.02), and portal blood flow (p=0.01) were predictive factors for EAD.

Conclusions

Non-invasive investigations of the liver microcirculation and hemoglobin oxygenation were shown to be predictive factors for EAD following liver transplantation.