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Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
Published on: March 11, 2017
Predicting hepatic steatosis and liver fat content in obese children based on biochemical parameters and
1Children's Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.
Insights
This study developed a liver fat score and equation using simple measurements to help doctors identify fatty liver disease in obese children. These tools accurately predict hepatic steatosis and liver fat content.
Area of Science:
- Pediatric Endocrinology
- Hepatology
- Medical Imaging
Background:
- Predicting hepatic steatosis and liver fat content (LFC) in obese children using general practice data is challenging.
- Limited understanding of reliable clinical and laboratory predictors for pediatric fatty liver disease.
Purpose of the Study:
- To develop predictive models for hepatic steatosis and LFC in obese children.
- Utilize biochemical parameters and anthropometry for model development.
Main Methods:
- Proton magnetic resonance spectroscopy used to quantify hepatic steatosis and LFC in 171 obese children.
- Analysis included routine clinical, laboratory parameters, and anthropometric measurements.
- Multivariate regression models created to develop a liver fat score and equation.
Main Results:
- A predictive model for hepatic steatosis, using waist circumference and alanine aminotransferase, achieved an AUC of 0.959.
- The model demonstrated high sensitivity (93%) and specificity (90%) for detecting hepatic steatosis.
- A liver fat equation was derived from the same parameters to calculate individual LFC.
Conclusions:
- A liver fat score and equation using routinely available variables can aid pediatricians in assessing hepatic steatosis and LFC.
- External validation is recommended prior to clinical implementation of these tools.
Background:
Predictors of quantitative evaluation of hepatic steatosis and liver fat content (LFC) using clinical and laboratory variables available in the general practice in the obese children are poorly identified.
Objective:
To build predictive models of hepatic steatosis and LFC in obese children based on biochemical parameters and anthropometry.
Methods:
Hepatic steatosis and LFC were determined using proton magnetic resonance spectroscopy in 171 obese children aged 5.5-18.0 years. Routine clinical and laboratory parameters were also measured in all subjects. Group analysis, univariable correlation analysis, and multivariate logistic and linear regression analysis were used to develop a liver fat score to identify hepatic steatosis and a liver fat equation to predict LFC in each subject.
Results:
The predictive model of hepatic steatosis in our participants based on waist circumference and alanine aminotransferase had an area under the receiver operating characteristic curve of 0.959 (95% confidence interval: 0.927-0.990). The optimal cut-off value of 0.525 for determining hepatic steatosis had sensitivity of 93% and specificity of 90%. A liver fat equation was also developed based on the same parameters of hepatic steatosis liver fat score, which would be used to calculate the LFC in each individual.
Conclusions:
The liver fat score and liver fat equation, consisting of routinely available variables, may help paediatricians to accurately determine hepatic steatosis and LFC in clinical practice, but external validation is needed before it can be employed for this purpose.
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