Introduction: Non-Alcoholic Fatty liver disease (NAFLD) is under-recognized in Primary care clinics. Early diagnosis in Primary care clinics is essential to help understand the magnitude of the burden and initiate measures to prevent its silent progression. With the rising incidence of NAFLD, it will soon become a major health care burden in the future. We aim to establish a screening algorithm for early detection of NAFLD and educate patients on primary preventive measures to avoid the development of cirrhosis from fatty liver. Methods: We created an algorithm that was tested in a cohort of patients recruited from the primary care center. Inclusion criteria: Presence of established Type two diabetes Mellitus (T2DM),Components of metabolic syndrome like BMI >27, CAD and dyslipidemia etc, Elevated Liver Enzymes or history of fatty liver by any imaging modality. Exclusion criteria : Alcoholics, known liver disease from other causes. Clinical and demographic data collected were age, sex, BMI, comorbidities, and lab results to calculate Fibrosis-4 and AST to Platelet Ratio Index (APRI) Scores. Patients with FIB-4 score greater than 1.45 and APRI score greater than 0.7 were instructed to get Fibroscan. Results: Between August 2020 and October 2021, 203 patients were screened in the primary care clinic for NAFLD. A total of 51 patients met the inclusion and exclusion criteria. A total of 7 people (13%) had insufficient data. The median age in our study was 60 years. In terms of comorbidities, 52 % had T2DM, 77 % had hypertension, 52 % had hyperlipidemia, and the median for the BMI over 30.9. 9% had APRI score between 0.7 and 0.99, and 16% had an APRI score of > 1. 34% of our patients had their FIB-4 index between 1.45 and 3.25 and the remaining 16% had a FIB-4 index more than 3.25. A total of 26 patients had a Fibroscan to determine the stage. The Kpa ranges between 5.3-7.2 and the CPA ranges between 246 and 361 dB/m. Patients with high APRI and FIB-4 score and abnormal fibroscan results are referred to Liver clinic for further management. (Figure) Conclusion: This study demonstrates that a stepwise prospective application of an algorithm using inclusion and exclusion criteria in clinical practice settings can lead to the early identification of patients with NAFLD. Increasing awareness among health care providers to implement screening strategies in Clinics is necessary. Further studies on implementation in larger size populations are needed along with education and long-term management of these patients. (Table)Figure 1.: Algorithm followed for the study Table 1. - Demographic and Clinical data of the study Demographics Total Patients (44) Male, N (%) 22 (50) Age, (Median, IQR) 60, (54.5- 68) BMI, Median (IQR) 30.9, (27.97- 35.08) Comorbidities Hypertension N, (%) 34, (77) Diabetes N, (%) 23, (52) Dyslipidemia N, (%) 23, (52) Laboratory Parameters Aspartate Aminotransferase- U/L, (Median, IQR) 28 (19- 37) Alanine Aminotransferase- U/L, (Median, IQR) 27 (21- 44) Fibrosis Lab assessment FIB4 %(< 1.45, 1.45- 3.25, >3.25) 50, 34,16 APRI % (< 0.7, 0.7- 0.99, >1) 75, 9, 16 Non-Invasive imagingLiver Elastography (Range) 5.3- 7.2 kPa. 247- 361 CAP score (dB/m)
Read full abstract