Performance of scoring systems to predict mortality of patients with acute‐on‐chronic liver failure: A systematic review and meta‐analysis

Zheng, Yixiang; Zhong, Xiao Yan; Li, Yajun; Fan, Xue‐Gong

doi:10.1111/jgh.13786

Cited by 25 publications

(20 citation statements)

References 43 publications

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“…[5][6][7] Throughout this period, the MELD score has predicted mortality for a broad variety of liver diseases, particularly at the 90-day timepoint as it was designed, and allocation algorithms utilizing it have demonstrated reduced waitlist mortality and improved patient survival. 10,[13][14][15][16] However, the MELD itself and its overall performance over time have not been evaluated in the context of the changing demographics, etiologies, and medical therapies for liver disease. 10,[13][14][15][16] However, the MELD itself and its overall performance over time have not been evaluated in the context of the changing demographics, etiologies, and medical therapies for liver disease.…”

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confidence: 99%

“…[8][9][10][11][12] Various modifications, mostly based on the MELD, have been proposed over the years to address the MELD's shortcomings in certain conditions such as acute liver failure, acute-on-chronic liver failure, hepatorenal syndrome, bacterial infection, encephalopathy, and more. 10,[13][14][15][16] However, the MELD itself and its overall performance over time have not been evaluated in the context of the changing demographics, etiologies, and medical therapies for liver disease.…”

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confidence: 99%

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The decreasing predictive power of MELD in an era of changing etiology of liver disease

Godfrey

Malik

Lai

et al. 2019

American Journal of Transplantation

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The field of liver transplantation has shifted considerably in the MELD era, including changing allocation, immunosuppression, and liver failure etiologies, as well as better supportive therapies. Our aim was to evaluate the predictive accuracy of the MELD score over time. The United Network for Organ Sharing provided de‐identified data on 120 156 patients listed for liver transplant from 2002‐2016. The ability of the MELD score to predict 90‐day mortality was evaluated by a concordance (C‐) statistic and corroborated with competing risk analysis. The MELD score's concordance with 90‐day mortality has downtrended from 0.80 in 2003 to 0.70 in 2015. While lab MELD scores at listing and transplant climbed in that interval, score at waitlist death remained steady near 35. Listing age increased from 50 to 54 years. HCV‐positive status at listing dropped from 33 to 17%. The concordance of MELD and mortality does not differ with age (>60 = 0.73, <60 = 0.74), but is lower in diseases that are increasing most rapidly—alcoholic liver disease and non‐alcoholic fatty liver disease—and higher in those that are declining, particularly in HCV‐positive patients (HCV positive = 0.77; negative = 0.73). While MELD still predicts mortality, its accuracy has decreased; changing etiology of disease may contribute.

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confidence: 99%

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confidence: 99%

The decreasing predictive power of MELD in an era of changing etiology of liver disease

Godfrey

Malik

Lai

et al. 2019

American Journal of Transplantation

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“…Medical history includes hypertension; diabetes; CKD or cardiopulmonary bypass surgery; and complications of AKI including hyperkalemia, metabolic acidosis, heart failure, respiratory failure, shock, central nervous system failure, and gastrointestinal bleeding [25]. The laboratory data included red cell volume distribution width (RDW) [26], hemoglobin (Hb), platelet (PLT), serum albumin (Alb), blood urea nitrogen (BUN), total cholesterol (TC), baseline eGFR (we estimated GFR according to the MDRD equation [23] and expressed relative GFR in mL/min/1.73 m 2 recommended by ESUR [27]), total bilirubin (TBIL) [28], proteinuria, and AKI stage [29]. Drugs used within 48 h prior to or after exposure to contrast media included diuretics and nephroprotective drugs (N-acetylcysteine or sodium bicarbonate).…”

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confidence: 99%

Post-contrast acute kidney injury in a hospitalized population: short-, mid-, and long-term outcome and risk factors for adverse events

Cheng

Liu

et al. 2020

Eur Radiol

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Objectives To investigate the prognosis including major adverse kidney events within 30 days (MAKE30) and 90-day and 1-year adverse outcome in hospitalized patients with post-contrast acute kidney injury (PC-AKI) to identify high-risk factors. Methods This retrospective observational study included 288 PC-AKI patients selected from 277,898 patients admitted to hospitals from January 2015 to December 2015. PC-AKI was defined according to the 2018 guideline of European Society of Urogenital Radiology. Multivariable Cox regression and logistic regression analyses were used to analyze main outcome and risk factors. Results PC-AKI patients with AKI stage ≥ 2 had much higher incidence of MAKE30 than those with AKI stage 1 (RR = 7.027, 95% CI 4.918-10.039). Persistent renal dysfunction, heart failure, central nervous system failure, baseline eGFR < 60 mL/min/ 1.73 m 2 , oliguria or anuria, blood urea nitrogen ≥ 7.14 mmol/L, respiratory failure, and shock were independent risk factors of 90day or 1-year adverse prognosis (p < 0.05). Compared with transient renal dysfunction, PC-AKI patients with persistent renal dysfunction had a higher all-cause mortality rate (

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“…At present, there have actually no ideal models to predict short-term outcomes of patients with HBV-ACLF yet. Model of end-stage liver disease (MELD) and the modified type--MELD integrating sodium (MELD-Na)--have been gradually proposed [6][7][8] to predict prognosis of patients with ACLF, with moderate accuracy [9]. However, due to limited predictive accuracy, these scoring systems are still unsatisfactory [9,10].…”

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confidence: 99%

Artificial neural network-based models used for predicting 28- and 90-day mortality of patients with hepatitis B-associated acute-on-chronic liver failure

et al. 2020

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Background: This study aimed to develop prognostic models for predicting 28-and 90-day mortality rates of hepatitis B virus (HBV)-associated acute-on-chronic liver failure (HBV-ACLF) through artificial neural network (ANN) systems. Methods: Six hundred and eight-four cases of consecutive HBV-ACLF patients were retrospectively reviewed. Four hundred and twenty-three cases were used for training and constructing ANN models, and the remaining 261 cases were for validating the established models. Predictors associated with mortality were determined by univariate analysis and were then included in ANN models for predicting prognosis of mortality. The receiver operating characteristic curve analysis was used to evaluate the predictive performance of the ANN models in comparison with various current prognostic models. Results: Variables with statistically significant difference or important clinical characteristics were input in the ANN training process, and eight independent risk factors, including age, hepatic encephalopathy, serum sodium, prothrombin activity, γ-glutamyltransferase, hepatitis B e antigen, alkaline phosphatase and total bilirubin, were eventually used to establish ANN models. For 28-day mortality in the training cohort, the model's predictive accuracy (AUR 0.948, 95% CI 0.925-0.970) was significantly higher than that of the Model for End-stage Liver Disease (MELD), MELD-sodium (MELD-Na), Chronic Liver Failure-ACLF (CLIF-ACLF), and Child-Turcotte-Pugh (CTP) (all p < 0.001). In the validation cohorts the predictive accuracy of ANN model (AUR 0.748, 95% CI: 0.673-0.822) was significantly higher than that of MELD (p = 0.0099) and insignificantly higher than that of MELD-Na, CTP and CLIF-ACLF (p > 0.05). For 90-day mortality in the training cohort, the model's predictive accuracy (AUR 0.913, 95% CI 0.887-0.938) was significantly higher than that of MELD, MELD-Na, CTP and CLIF-ACLF (all p < 0.001). In the validation cohorts, the prediction accuracy of the ANN model (AUR 0.754, 95% CI: 0.697-0.812 was significantly higher than that of MELD (p = 0.019) and insignificantly higher than MELD-Na, CTP and CLIF-ACLF (p > 0.05).

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Performance of scoring systems to predict mortality of patients with acute‐on‐chronic liver failure: A systematic review and meta‐analysis

Cited by 25 publications

References 43 publications

The decreasing predictive power of MELD in an era of changing etiology of liver disease

The decreasing predictive power of MELD in an era of changing etiology of liver disease

Post-contrast acute kidney injury in a hospitalized population: short-, mid-, and long-term outcome and risk factors for adverse events

Artificial neural network-based models used for predicting 28- and 90-day mortality of patients with hepatitis B-associated acute-on-chronic liver failure

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