Metabolic dysfunction-associated fatty liver disease (MAFLD) formly called non alcoholic fatty liver disease (NAFLD) was defined as the presence of macrovesicular steatosis in ≥5% of hepatocytes in individuals who consume little or no alcohol. NAFLD was divided into two major subtypes: nonalcoholic fatty liver, and Non alcoholic steatohepatitis (NASH).
It is now believed that MAFLD is due to state of systemic metabolic dysfunction and is perceived as standalone disease that warrants positive diagnosis rather than simply a disease of exclusion. MAFLD affects about quarter of the world's population and it is now considered a public health issue.
Real time ultrasound (US) scanning is accepted as the first line imaging investigation in patients with suspected liver disorders. In spite insufficient sensitivity to detect liver inflammation and fibrosis, it demonstrates a good correlation with histological finding of fatty infiltration.
Another tool used for detection of fatty liver is fatty liver index (FLI) which is an algorithm based on waist circumference, body mass index (BMI), triglyceride, and gamma-glutamyl-transferase (GGT). A FLI \< 30 (negative likelihood ratio = 0.2) rules out and a FLI ≥ 60 (positive likelihood ratio = 4.3) rules in fatty liver. FLI had an accuracy of 0.84 (95% confidence interval (CI) 0.81-0.87) in detecting fatty liver.
Haung X, et al, 2015 found that FLI achieves a high sensitivity of 79.89% and a specificity of 71.51% for diagnosis of NAFLD.
TE (transient elastography) is a non-invasive ultrasound-based method that uses shear wave velocity to assess tissue (e.g., liver) stiffness. It has been applied in medical practice under the name FibroScan®.
Based on the physical characteristics (velocity and intensity attenuation) of the shear wave, the acquired data in the examination are processed and displayed on the screen as the liver stiffness measurement (LSM) and controlled attenuation parameter (CAP).
LSM values range from 1.5 to 75 kPa; lower values indicate a more elastic liver. CAP values range from 100 to 400 dB/m, and higher numbers indicate more pronounced steatosis.
A meta-analysis in 2014 has indicated that TE is excellent in diagnosing F ≥ 3 (85% sensitivity, 82% specificity) and F4 (92% sensitivity, 92% specificity), and it has a moderate accuracy for F ≥ 2 in NAFLD patients.
According to various studies, compared to liver biopsy, CAP is useful in the detection of S ≥ 1, S ≥ 2, and S3 (where S0 indicates no steatosis, to S3, which indicates the highest level of steatosis steatosis) because of its good sensitivity and specificity; however, the exact cut-off values remain to be defined.
Sample size estimation:
To assess the prevalence of MAFLD in, a prospective cross-sectional study was conducted. Based on previous studies (24), the expected frequency of MAFLD in Egypt is 37%. For a two-sided 95% confidence interval for a single proportion using the large sample normal approximation that will extend 5 % from the expected proportion, a sample size of 360 participant will be recruited. The sample will be equally represented from urban and rural areas. Sample size estimation was performed by Epi Info statistical package (Dean A, 1990).
Dean A (1990). Epi Info, Version 5.01. US Department of Health and Human Services, Public Health Service, Centers for Disease Control; 1990.
Statistical methods Data management and analysis will be performed using Statistical Package for Social Sciences (SPSS) vs. 25. Numerical data were summarized using means and standard deviations or medians, interquartile ranges and/or ranges, as appropriate. Categorical data were summarized as numbers and percentages. Estimates of the frequency of different grade of severity of NAFLD in the entire sample and will be done using the numbers and percentages. Numerical data were explored for normality using Kolmogrov-Smirnov test and Shapiro-Wilk test. The severity of fatty liver will be related to different serological risk factors of metabolic syndrome and diseases progression.
Chi square or Fisher's tests will be used to compare between the groups with respect to categorical data, as appropriate. Comparisons between two groups for normally distributed numeric variables will be done using the Student's t-test while for non-normally distributed numeric variables, comparisons will be done by Mann-Whitney test. Comparisons between more than 2 groups will be performed by the one analysis of variance (ANOVA) for normally distributed variables and Kruskal-Wallis for non-normally distributed variables, then followed by post hoc if needed. To measure the strength of association between the normally distributed numerical measurements, Pearson's correlation coefficients will be computed. Spearman's correlation coefficients will be calculated for non-normally distributed variables. All tests are two-sided. P-values \< 0.05 is considered significant.
