Predicting outcome on admission and post-admission for acetaminophen-induced acute liver failure using classification and regression tree models.

Jaime Lynn Speiser,Constantine J Karvellas,William M Lee,Gustavo Batista Menezes

doi:10.1371/journal.pone.0122929

Abstract

Background/AimAssessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients often presents significant challenges. King’s College (KCC) has been validated on hospital admission, but little has been published on later phases of illness. We aimed to improve determinations of prognosis both at the time of and following admission for APAP-ALF using Classification and Regression Tree (CART) models.MethodsCART models were applied to US ALFSG registry data to predict 21-day death or liver transplant early (on admission) and post-admission (days 3-7) for 803 APAP-ALF patients enrolled 01/1998–09/2013. Accuracy in prediction of outcome (AC), sensitivity (SN), specificity (SP), and area under receiver-operating curve (AUROC) were compared between 3 models: KCC (INR, creatinine, coma grade, pH), CART analysis using only KCC variables (KCC-CART) and a CART model using new variables (NEW-CART).ResultsTraditional KCC yielded 69% AC, 90% SP, 27% SN, and 0.58 AUROC on admission, with similar performance post-admission. KCC-CART at admission offered predictive 66% AC, 65% SP, 67% SN, and 0.74 AUROC. Post-admission, KCC-CART had predictive 82% AC, 86% SP, 46% SN and 0.81 AUROC. NEW-CART models using MELD (Model for end stage liver disease), lactate and mechanical ventilation on admission yielded predictive 72% AC, 71% SP, 77% SN and AUROC 0.79. For later stages, NEW-CART (MELD, lactate, coma grade) offered predictive AC 86%, SP 91%, SN 46%, AUROC 0.73.ConclusionCARTs offer simple prognostic models for APAP-ALF patients, which have higher AUROC and SN than KCC, with similar AC and negligibly worse SP. Admission and post-admission predictions were developed.Key Points• Prognostication in acetaminophen-induced acute liver failure (APAP-ALF) is challenging beyond admission• Little has been published regarding the use of King’s College Criteria (KCC) beyond admission and KCC has shown limited sensitivity in subsequent studies• Classification and Regression Tree (CART) methodology allows the development of predictive models using binary splits and offers an intuitive method for predicting outcome, using processes familiar to clinicians• Data from the ALFSG registry suggested that CART prognosis models for the APAP population offer improved sensitivity and model performance over traditional regression-based KCC, while maintaining similar accuracy and negligibly worse specificity• KCC-CART models offered modest improvement over traditional KCC, with NEW-CART models performing better than KCC-CART particularly at late time points

Highlights

Acetaminophen (APAP) is the most common cause of acute liver failure (ALF) in Europe and North America [1, 2]
We aimed to develop Classification and Regression Tree (CART) models that offered higher sensitivity, while maintaining similar overall accuracy, compared to traditional King’s College Criteria (KCC) by using a weighted sampling scheme to split admission and post-admission datasets
NEW-CART models developed in this study offer similar predictive performance on admission compared to traditional KCC and KCC-CART, but included Model for End-Stage Liver Disease (MELD), which must be calculated prior to prediction

Summary

Introduction

Acetaminophen (APAP) is the most common cause of acute liver failure (ALF) in Europe and North America [1, 2]. Despite reasonable post-transplant outcomes, liver transplantation (LT) for acetaminophen-induced acute liver failure (APAP-ALF) often presents significant challenges in management due to the rapidity and severity of illness, the potential for recovery without LT and the presence of complex psychosocial issues in most patients [3, 4]. Data from the US ALFSG shows that approximately 25% of APAP patients are listed for LT and less than 10% receive LT [5]. Current data suggest that APAP recovery for many patients is determined by 3–4 days following onset of illness [6]. While the King’s College Criteria (KCC) [9] and Clichy criteria [10] have been validated on admission, prediction of outcome at later time points appears less accurate [11] when hepatic dysfunction would be characterized primarily by immunosuppression rather than multi-organ failure [8]

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