Analysis of risk factors for fatty liver disease in children with Wilson's disease

Abstract

Background and aims: Many children with Wilson's disease are complicated with dyslipidemia. The aim of this study was to investigate the risk factors for the development of fatty liver disease (FLD) in children with Wilson's disease.

Methods: We evaluated sex, age, weight, the disease course, treatment course, clinical classification, alanine transaminase (ALT), aspartate transaminase, γ-glutamyl transpeptidase, total biliary acid, triglyceride, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, homocysteine, uric acid, fibrinogen (FBG), creatinine, procollagen III N-terminal propeptide, laminin, hyaluronic acid, type IV collagen, and performed receiver operating characteristic curve analysis to investigate the forecast value of individual biochemical predictors and combined predictive indicators to evaluate FLD in Wilson's disease.

Results: The multivariate logistic regression analysis revealed that ALT [odds ratio (OR), 1.011; 95% confidence interval (CI), 1.004-1.02; P = 0.006], uric acid (OR, 1.01; 95% CI, 1.002-1.018; P = 0.017), FBG (OR, 3.668; 95% CI, 1.145-13.71; P = 0.037), creatinine (OR, 0.872; 95% CI, 0.81-0.925; P < 0.001), and laminin (OR, 1.01; 95% CI, 1.002-1.018; P = 0.017) acted as independent risk factors in Wilson's disease complicated with FLD. The receiver operating characteristic curves for combined predictive indicators demonstrated an area under the curve values of 0.872, which was found to be a significant predictors for FLD in Wilson's disease.

Conclusions: We screened out the most important risk factors, namely ALT, uric acid, creatinine, FBG, and laminin for Wilson's disease complicated with FLD. The joint prediction achieved is crucial for identifying children with Wilson's disease complicated with FLD.

Fig. 1.

WD diagnostic process [15]. WD, Wilson’s disease.

Fig. 2.

Forest plot of each factor. The left column lists the factors. The odds ratio for each of these studies is represented by a square, and confidence intervals are represented by horizontal lines. ALT, alanine transaminase; AST, aspartate transaminase; CIV, type IV collagen; CREA, creatinine; FBG, fibrinogen; GGT, γ-glutamyl transpeptidase; HA, hyaluronic acid; HCY, homocysteine; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LN, laminin; OR, odds ratio; PIIINP, procollagen III N-terminal propeptide; TBA, total biliary acid; TG, triglyceride; UA, uric acid.

Fig. 3.

ROC curve depicting the predictive efficacy of each predictor for FLD. Sensitivity measurements are on the y-axis, and 1 − specificity is on the x-axis. The area under the curve represents the prediction accuracy. The optimal cutoff for each predictor was defined using the SPSS software. AUC = 0.872. ALT, alanine transaminase; AUC, area under curve; CPI, combined predictive indicators; CREA, creatinine; FBG, fibrinogen; FLD, fatty liver disease; LN, laminin; ROC, receiver operating characteristic; UA, uric acid.