Early Acute Kidney Injury Associated with Liver Transplantation: A Retrospective Case-Control Study

A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study

BACKGROUND

Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication following noncardiac surgery and is associated with increased mortality. Early identification of geriatric patients at high risk of AKI could facilitate preventive measures and improve patient prognosis. This study used machine learning methods to identify important features and predict AKI following noncardiac surgery in geriatric patients.

METHODS

The data for this study were obtained from a prospective cohort. Patients aged ≥ 65 years who received noncardiac surgery from June 2019 to December 2021 were enrolled. Data were split into training set (from June 2019 to March 2021) and internal validation set (from April 2021 to December 2021) by time. The least absolute shrinkage and selection operator (LASSO) regularization algorithm and the random forest recursive feature elimination algorithm (RF-RFE) were used to screen important predictors. Models were trained through extreme gradient boosting (XGBoost), random forest, and LASSO. The SHapley Additive exPlanations (SHAP) package was used to interpret the machine learning model.

RESULTS

The training set included 6753 geriatric patients. Of these, 250 (3.70%) patients developed AKI. The XGBoost model with RF-RFE selected features outperformed other models with an area under the precision-recall curve (AUPRC) of 0.505 (95% confidence interval [CI]: 0.369-0.626) and an area under the receiver operating characteristic curve (AUROC) of 0.806 (95%CI: 0.733-0.875). The model incorporated ten predictors, including operation site and hypertension. The internal validation set included 3808 geriatric patients, and 96 (2.52%) patients developed AKI. The model maintained good predictive performance with an AUPRC of 0.431 (95%CI: 0.331-0.524) and an AUROC of 0.845 (95%CI: 0.796-0.888) in the internal validation.

CONCLUSIONS

This study developed a simple machine learning model and a web calculator for predicting AKI following noncardiac surgery in geriatric patients. This model may be a valuable tool for guiding preventive measures and improving patient prognosis.

TRIAL REGISTRATION

The protocol of this study was approved by the Committee of Ethics from West China Hospital of Sichuan University (2019-473) with a waiver of informed consent and registered at www.chictr.org.cn (ChiCTR1900025160, 15/08/2019).

Impact of patent foramen ovale on short-term outcomes in children with biliary atresia undergoing living donor liver transplantation: a retrospective cohort study

OBJECTIVE

To investigate the impact of patent foramen ovale (PFO) on the short-term outcomes of living donor liver transplantation (LDLT) in children with biliary atresia.

METHODS

With the approval of the hospital ethics committee, 304 children with biliary atresia who underwent LDLT in our center from January 2020 to December 2021 were enrolled. According to the results of echocardiography before the operation, the subjects were divided into the PFO group (n = 73) and the NoPFO group (n = 231). The baseline characteristics; intraoperative recipient-related data and donor-related data; incidence of postreperfusion syndrome (PRS); postoperative mechanical ventilation time; ICU stay duration; postoperative hospital stay duration; liver function index; incidences of postoperative complications including acute renal injury (AKI), graft dysfunction, hepatic artery thrombosis (HAT) and portal vein thrombosis (PVT); and one-year survival rate were compared between the two groups.

RESULTS

The median age in the PFO group was 6 months and that in the NoPFO group was 9 months (P < 0.001), and the median height (65 cm) and weight (6.5 kg) in the PFO group were significantly lower than those in the NoPFO group (68 cm, 8.0 kg) (P < 0.001). The preoperative total bilirubin level (247 vs. 202 umol/L, P = 0.007) and pediatric end-stage liver disease (PELD) score (21 vs. 16, P = 0.001) in the PFO group were higher than those in the NoPFO group. There were no significant differences in the intraoperative PRS incidence (46.6% vs. 42.4%, P = 0.533 ), postoperative mechanical ventilation time (184 vs. 220 min, P = 0.533), ICU stay duration (3.0 vs. 2.5 d, P = 0.267), postoperative hospital stay duration (22 vs. 21 d, P = 0.138), AKI incidence (19.2% vs. 24.7%, P = 0.333), graft dysfunction incidence (11.0% vs. 12.6%, P = 0.716), HAT incidence (5.5% vs. 4.8%, P = 0.762), PVT incidence (2.7% vs. 2.2%, P = 0.675) or one-year survival rate (94.5% vs. 95.7%, P = 0.929) between the two groups.

CONCLUSION

The presence of PFO has no negative impact on short-term outcomes in children with biliary atresia after LDLT.

Impact of Sirolimus versus Mycophenolate Mofetil on Kidney Function after Calcineurin Inhibitor Dose Reduction in Liver Transplant Recipients

Impaired kidney function is associated with increased morbidity and mortality in patients undergoing liver transplantation. Although immunosuppressants are essential in these patients, they impair kidney function. This study aimed to compare adverse kidney outcomes between patients treated with a reduced dose of tacrolimus (calcineurin inhibitor) plus sirolimus or mycophenolate mofetil (MMF) in the liver transplant center at Kaohsiung Chang Gung Memorial Hospital between April 2011 and December 2017. Propensity score matching was used to identify 232 patients. The risk of adverse kidney outcomes was estimated using Cox proportional hazards regression, and changes in kidney function over time were analyzed using linear mixed modeling. Acute kidney disease risks in this study cohort were not significantly different for the two immunosuppressants (aHR 1.04; 95% CI: 0.70-1.55, p = 0.8328). However, sirolimus use was significantly associated with a higher risk of estimated glomerular filtration rate decline > 30% than MMF (aHR, 2.09; 95% CI: 1.33-3.28; p = 0.0014). Our results demonstrate that sirolimus use may have worsened long-term kidney outcomes compared to MMF. Close monitoring of kidney function, dose adjustment, and timely transition to MMF is necessary for LT patients receiving sirolimus.

Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation

BACKGROUND

We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT).

METHODS

A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort according to the time of inclusion. Univariable and multivariable logistic regression using the forward variable selection routine were applied to find risk factors for post-OLT severe AKI. Based on the results of multivariable analysis, a nomogram was developed and validated. Patients were followed up to assess the long-term mortality and development of chronic kidney disease (CKD).

RESULTS

Overall, 35.9% of patients were diagnosed with severe AKI. Multivariable logistic regression analysis revealed that recipients' BMI (OR 1.10, 95% CI 1.04-1.17, p = 0.012), hypertension (OR 2.32, 95% CI 1.22-4.45, p = 0.010), preoperative serum creatine (sCr) (OR 0.96, 95% CI 0.95-0.97, p < 0.001), and intraoperative fresh frozen plasm (FFP) transfusion (OR for each 1000 ml increase 1.34, 95% CI 1.03-1.75, p = 0.031) were independent risk factors for post-OLT severe AKI. They were all incorporated into the nomogram. The area under the ROC curve (AUC) was 0.73 (p < 0.05) and 0.81 (p < 0.05) in the development and validation cohort. The calibration curve demonstrated the predicted probabilities of severe AKI agreed with the observed probabilities (p > 0.05). Kaplan-Meier survival analysis showed that patients in the high-risk group stratified by the nomogram suffered significantly poorer long-term survival than the low-risk group (HR 1.92, p < 0.01). The cumulative risk of CKD was higher in the severe AKI group than no severe AKI group after competitive risk analysis (HR 1.48, p < 0.05).

CONCLUSIONS

With excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for severe AKI and poor long-term prognosis after OLT.

Acute Kidney Injury After Liver Transplant: Incidence, Risk Factors, and Impact on Patient Outcomes

OBJECTIVES

Acute kidney injury is a frequent complication of liver transplant. Here, we assessed the rate and contributing factors of acute kidney injury and need for renal replacement therapy in patients undergoing liver transplant at a transplant center in Tehran, Iran.

MATERIAL AND METHODS

We identified all patients who underwent liver transplant at the Imam Khomeini Hospital Complex from March 2018 to March 2019 and who were followed for 3 months after transplant. Acute kidney injury was defined based on the Acute Kidney Injury Network criteria. We collected demographic and pretransplant, intraoperative, and posttransplant data. Univariable and multivariable models were applied to explore independent risk factors for acute kidney injury incidence and need for renal replacement therapy.

RESULTS

Our study included 173 deceased donor liver transplant recipients. Rates of incidence of acute kidney injury and need for renal replacement therapy were 68.2% and 14.5%, respectively. The 3-month mortality rate among those with severe and mild or moderate acute kidney injury was 44.0% (14/25) and 9.7% (9/ 93), respectively (P < .001). Multivariable analyses indicated that serum albumin (relative risk of 0.55; 95% confidence interval, 0.34-0.87; P = .021), baseline serum creatinine (relative risk of 2.11; 95% confidence interval, 1.56-2.90; P = .037), and intraoperative mean arterial pressure (relative risk of 0.76; 95% confidence interval, 0.63-0.82; P = .008) were independent factors for predicting posttransplant acute kidney injury. Independent risk factors for requiring renal replacement therapy were pretransplant serum creatinine (relative risk of 1.99; 95% confidence interval, 1.89-4.47; P = .044) and intraoperative vasopressor infusion (relative risk of 1.41; 95% confidence interval, 1.38-2.00; P = .021).

CONCLUSIONS

We found a high incidence of acute kidney injury among liver transplant recipients in our center. There was a significant association between severity of acute kidney injury and 3-month and in-hospital mortality.

Risk Factors and Prognosis of New-Onset Chronic Kidney Disease Following Orthotopic Liver Transplantation: A Retrospective Case-Control Study

Background

We have undertaken this investigation to explore the perioperative risk factors of new-onset chronic kidney disease (NOCKD) after orthotopic liver transplantation (OLT), and to provide an early prediction model for the screening of NOCKD high-risk populations.

Material/Methods

A retrospective case-control study was performed in adult recipients who received OLT in our center between January 2018 and January 2020. Perioperative data were collected using the center’s electronic medical record system. Logistics regression analysis was used to determine risk factors for NOCKD within 1 year following OLT. Kaplan-Meier and log-rank tests were used to evaluate the 1-year survival of recipients with NOCKD or without NOCKD.

Results

A total of 174 patients were included in this study, and 29 patients developed NOCKD after OLT. Logistic multivariate regression analysis showed that preoperative diabetes, high model for end-stage liver disease (MELD) score, postoperative acute kidney injury (AKI), and postoperative renal replacement therapy (RRT) were independent risk factors for NOCKD 1 year after OLT. The 1-year survival rate of NOCKD recipients waas significantly lower than that of patients who did not receive NOCKD.

Conclusions

Diabetes mellitus, MELD score, postoperative AKI, and requirement for postoperative RRT are independent risk factors for NOCKD after OLT, which may have great potential for personalized decision making and predicting the 1-year postoperative mortality of the recipient.