This fatty liver index (FLI) for hepatic steatosis calculator helps diagnosis FL based on patient BMI, triglycerides, GGT and waist circumference for referral to ultrasonography. There are instructions on the calculation method used and more information on the original study in the text below the form.
How does the fatty liver index (FLI) for hepatic steatosis calculator work?
This health tool is based on the Fatty Liver Index (FLI) of Bedogni et al. and aims to facilitate the identification of patients with fatty liver disease from the general population. The original study developed in 2006 used data from the Dionysos Nutrition & Liver Study.
It refers to fatty liver disease, either caused by ethanol intake (which is called non-alcoholic fatty liver disease (NAFLD)) or not.
The diagnosis of FL was made through ultrasonography and the subjects also kept a 7-day record of their alcohol intake. Firstly, 13 variables were deemed as potential predictors of the liver disease:
■ Ethanol intake;
■ Alanine transaminase;
■ Aspartate transaminase;
■ Gamma-glutamyl-transferase (GGT);
■ Body mass index (BMI);
■ Waist circumference;
■ Sum of 4 skinfolds;
The study resulted in the creation of an algorithm comprising of the following parameters, also present in the fatty liver index for hepatic steatosis calculator:
■ BMI – body mass index, measured in kg per square meter. This is used as a surrogate measure for body adiposity.
■ Waist circumference – measured in centimeters and based on recent data showing its connection to fatty liver.
■ GGT – gamma-glutamyl transpeptidase, measured in IU/L which is an enzyme that catalyzes some metabolic processes in the gamma-glutamyl cycle. It is predominantly found in liver tissue and is used as a diagnosis marker for hepatic illnesses.
The formula that calculates the probability of fatty liver disease occurrence is:
FLI = (e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference - 15.745) / (1 + e0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference - 15.745) x 100
The parameters that are used to create the formula are:
|ß||SE (ß)||STD (ß)||p|
|Loge (triglycerides, mg/dL)||0.953||0.211||0.308||<0.0001|
|Loge (GGT, U/L)||0.718||0.202||0.278||<0.0001|
|Waist circumference (cm)||0.053||0.019||0.356||0.005|
Hepatic steatosis refers to the inflammation that follows the accumulation of abnormal quantities of lipids in the liver cells and the subsequent disturbance in the fat metabolism. Another association is made between the fatty liver symptoms and the metabolic syndrome (presence of diabetes, hypertension, obesity etc).
The fatty liver index ranges between 1 and 100, and the interpretation of the three intervals within this range is the following:
■ FLI below 30 means that FL is ruled out (with a negative likelihood ratio of up to 0.2);
■ FLI between 30 and below 60 is inconclusive;
■ FLI of 60 and above means that FL is present (with a positive likelihood ratio starting from 4.3).
The table below introduces the statistical values for the extended fatty liver index intervals:
|FLI cut-point||% patients||Sensitivity||Specificity||Positive likelihood ratio||Negative likelihood ratio|
The results from the index calculation allow clinicians to plan which of the patients need access to liver ultrasonography.
The above algorithm showed a 0.84 (95%CI 0.81–0.87) accuracy in detecting FL. It is also considered a surrogate marker of nonalcoholic fatty liver disease (NAFLD).
A further validation study has looked at whether the FLI has any predictive value for diabetes mellitus (DM). This is especially important as type 2 diabetes and hypertriglyceridemia are main causes for the occurrence of FL, with alcohol consumption playing a less significant role.
1) Bedogni G, Bellentani S, et al. (2006) . BMC Gastroenterology.
2) Cuthbertson DJ, Weickert MO, Lythgoe D, Sprung VS, Dobson R, Shoajee-Moradie F, Umpleby M, Pfeiffer AF, Thomas EL, Bell JD, Jones H, Kemp GJ. (2014) . Eur J Endocrinol; 171(5):561-9.
3) Huang X, Xu M, Chen Y, Peng K, Huang Y et al. (2015) . Medicine (Baltimore); 94(40): e1682.
4) Motamed N, Sohrabi M, Ajdarkosh H, Hemmasi G, Maadi M, Sima F et al. (2016) . World J Gastroenterol; 22(10): 3023–3030.16 Oct, 2016