Development and validation of a multivariable prediction model in pediatric liver transplant patients for predicting intensive care unit length of stay

Abstract

BackgroundLiver transplantation is the life‐saving treatment for many end‐stage pediatric liver diseases. The perioperative course, including surgical and anesthetic factors, have an important influence on the trajectory of this high‐risk population. Given the complexity and variability of the immediate postoperative course, there would be utility in identifying risk factors that allow prediction of adverse outcomes and intensive care unit trajectories.AimsThe aim of this study was to develop and validate a risk prediction model of prolonged intensive care unit length of stay in the pediatric liver transplant population.MethodsThis is a retrospective analysis of consecutive pediatric isolated liver transplant recipients at a single institution between April 1, 2013 and April 30, 2020. All patients under the age of 18 years receiving a liver transplant were included in the study (n = 186). The primary outcome was intensive care unit length of stay greater than 7 days.ResultsRecipient and donor characteristics were used to develop a multivariable logistic regression model. A total of 186 patients were included in the study. Using multivariable logistic regression, we found that age < 12 months (odds ratio 4.02, 95% confidence interval 1.20–13.51, p = .024), metabolic or cholestatic disease (odds ratio 2.66, 95% confidence interval 1.01–7.07, p = .049), 30‐day pretransplant hospital admission (odds ratio 8.59, 95% confidence interval 2.27–32.54, p = .002), intraoperative red blood cells transfusion >40 mL/kg (odds ratio 3.32, 95% confidence interval 1.12–9.81, p = .030), posttransplant return to the operating room (odds ratio 11.45, 95% confidence interval 3.04–43.16, p = .004), and major postoperative respiratory event (odds ratio 32.14, 95% confidence interval 3.00–343.90, p < .001) were associated with prolonged intensive care unit length of stay. The model demonstrates a good discriminative ability with an area under the receiver operative curve of 0.888 (95% confidence interval, 0.824–0.951).ConclusionsWe develop and validate a model to predict prolonged intensive care unit length of stay in pediatric liver transplant patients using risk factors from all phases of the perioperative period.

Prediction of early recovery of graft function after living donor liver transplantation in children

“…As a visual, personalized and convenient tool, the nomogram has been increasingly used in medical research, such as predicting the prognosis of malignancies, treatment efficacy and other medical activities 38 – 40 . However, there are only a few application researches of predictive models in pediatric LT, such as predicting the length of length of stay in intensive care unit, the incidence of late-onset acute cellular rejection, the incidence of ischemic-type biliary lesions and postoperative survival rate 41 – 45 . In this study, we constructed the first predictive model with several simple indicators to evaluate the early recovery of graft function in children after LDLT.…”

Risk association paradox after pediatric liver transplantation: Can we identify the causes that bring back patients to the operating room?

“…We have read with great interest the work by Siddiqui et al 1 who developed a multivariable model to predict the length of stay (LOS) in the intensive care unit (ICU) after pediatric liver transplantations.…”

Postoperative outcomes after pediatric liver transplantation

“…We read with interest the recent report by Siddiqui et al 1 regarding the development of a multivariable prediction model for prolonged ICU length of stay for children who have undergone liver transplantation. Anesthesia for pediatric liver transplantation is one of the most complex types of anesthesia that we provide.…”

“…We read with interest the recent report by Siddiqui et al 1 . regarding the development of a multivariable prediction model for prolonged ICU length of stay for children who have undergone liver transplantation.…”