Incidence and Early Detection of Patients with Nonalcoholic Fatty Liver Disease Referred to the Gastroenterology Clinic: A QI Project

Saraswathi Lakkasani, MD*¹, Rime Mehannek, MD¹, GoWthami Sai Kogilathota Jagirdhar, MD ¹, Benjamin Weber, DO ¹, Shawn Guptha, MD¹, Afshan Tabassum, MD ¹, Mahidhar M Reddy, MD ¹, Yatinder Bains, MD ¹

1. Saint Michael’s Medical Center in affiliation with New York Medical College, Newark, New Jersey.

Corresponding Author: Saraswathi Lakkasani, MD, Saint Michael’s Medical Center in affiliation with New York Medical College, Newark, New Jersey.

Copy Right: © 2022 Saraswathi Lakkasani, MD, This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received Date: November 24, 2022

Published Date: December 01, 2022

Introduction

Non-Alcoholic Fatty liver disease is under-recognized in Primary care clinics. Patients with Non-alcoholic fatty liver disease is predisposed to Liver Cirrhosis and Cancer in the long

Term. 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.

Aim

We aim to establish a screening algorithm for early detection of non-alcoholic fatty liver disease (NAFLD) in Primary care clinics 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 and the inpatient settings of the hospital. (Figure 1) We created a fishbone diagram to help the screening algorithm which served as the foundation of the study. The fishbone diagram evolved to meet the needs and challenges faced in our Primary care Clinic. (Figure 2)

Inclusion criteria were:

1. Presence of established Type two diabetes Mellitus (T2DM)
2. Components of metabolic syndrome like hypertension and dyslipidemia
3. Elevated aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels or history of fatty liver by any imaging modality.

Exclusion criteria were:

• Other causes of chronic liver disease.
• Clinical and demographic data collected were age, sex, BMI, comorbidities, and laboratory parameters to calculate Fibrosis-4 and AST to Platelet Ratio Index (APRI) Scores.
• Patients with Fibrosis-4 score greater than 1.3 and APRI score greater than 0.7 were referred to a gastroenterology clinic for Liver Elastography (Fibroscan).

Results

• Between August 2020 and October 2021, 203 patients were screened in the primary care clinic for NAFLD. (Figure 3 & Table 1)
• 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, with 22 (50%) males.
• In terms of comorbidities, 52 % had T2DM, 77 % had hypertension, 52 % had hyperlipidemia, and the median for the BMI over 30.9.
• 75% of our patients had an APRI score of less than 0.7, 9% had an APRI score between 0.7 and 0.99, and 16% had an APRI score of > 1.
• The FIB-4 index was divided into three categories.
• Half of our patients had a FIB-4 index of less than 1.45, 34% of our patients  had their FIB-4 index  ranges between 1.45 and 3.25  and the remaining 16% had a FIB-4 index of more than 3.25.
• Of those patients, a total of 26 patients had a Liver Elastography to determine the stage. The Kpa ranges between 5.3-7.2 and the CPA ranges between 246 and 361 dB/m.

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.

Figure 1

Figure 2

Figure 3