Automated Fibrosis-4 Index: Simplifying Non-Alcoholic Fatty Liver Disease for Diabetologists

Author:

Ismail Mona H.12ORCID,Al Argan Reem23ORCID,Elamin Yasir23,Makki Murtaga1,Alsheekh Lameya1,Alelyani Jaber1,Hadhiah Zahra3ORCID,Aljidhr Zahrah1,Alkhatam Nazih3ORCID,Alfaddagh Hind1,Alanazi Alanoud23,Alqahtani Shaya24ORCID

Affiliation:

1. Division of Gastroenterology, Department of Internal Medicine, King Fahd Hospital of the University, Al-Khobar 31952, Saudi Arabia

2. College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia

3. Division of Endocrine, Department of Internal Medicine, King Fahd Hospital of the University, Al-Khobar 31952, Saudi Arabia

4. Department of Internal Medicine, King Fahd Hospital of the University, Al-Khobar 31952, Saudi Arabia

Abstract

Background and Objectives: Patients with type 2 diabetes (T2D) have a high prevalence of non-alcoholic fatty liver disease (NAFLD) (55%) and are at increased risk for developing non-alcoholic steatohepatitis, a severe form of NAFLD. Early detection of advanced fibrosis in patients with T2D and NAFLD is crucial and can prevent progression to chronic liver disease, cirrhosis, and hepatocellular carcinoma. However, screening for liver disease and risk-stratification pathways are not established in patients with T2D. We evaluated the efficacy of using the automated fibrosis-4 (FIB-4) index in routine clinical settings to identify patients requiring further specialist evaluation. Materials and Methods: In this prospective cohort study, individuals diagnosed with T2D were recruited from diabetes clinics at a tertiary university hospital. Demographic, clinical, and laboratory data were comprehensively collected. The FIB-4 index was automatically calculated and integrated into the hospital’s electronic medical records (EMRs), which were then stratified by age. Patients with advanced fibrosis (FIB-4 index ≥ 1.3) were referred to a specialist. Student’s t-test or the Mann–Whitney U test was used to analyze variables associated with advanced fibrosis. Logistic regression was used to identify predictors of advanced fibrosis. Results: Among the 318 patients with T2D, 9.7% had advanced fibrosis. The majority were females (54.7%) and Saudi nationals (89.6%). Several factors, including age, platelet count, total bilirubin, serum albumin, total cholesterol, low-density lipoprotein, transaminases, and gamma-glutamyl transferase (GGT), showed significant associations with advanced fibrosis (all p < 0.05). Older age, elevated total bilirubin and GGT levels, and prolonged international normalized ratio emerged as independent predictors of advanced fibrosis. Conclusions: Integrating the FIB-4 index into the EMR during the routine care of patients with T2D proved to be a valuable tool in effectively identifying individuals at risk of advanced fibrosis. Our findings emphasize the need for further research to refine screening strategies in this high-risk population.

Publisher

MDPI AG

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