Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Aug 27, 2022; 14(8): 1598-1607
Published online Aug 27, 2022. doi: 10.4254/wjh.v14.i8.1598
Simple diagnostic algorithm identifying at-risk nonalcoholic fatty liver disease patients needing specialty referral within the United States
Naim Alkhouri, Pankaj Aggarwal, Phuc Le, Julia Payne, Celine Sakkal, Prido Polanco, Stephen Harrison, Mazen Noureddin
Naim Alkhouri, Pankaj Aggarwal, Celine Sakkal, Prido Polanco, Department of Hepatology, Arizona Liver Health, Chandler, AZ 85712, United States
Phuc Le, Julia Payne, Center for Value-Based Care Research, Cleveland Clinic, Cleveland, OH 44195, United States
Stephen Harrison, Department of Research, Pinnacle Research, San Antonio, TX 78229, United States
Mazen Noureddin, Department of Hepatology, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States
Author contributions: Alkhouri N, Sakkal C, and Polanco P contributed to the data collection; Le P and Payne J contributed to the data collection; Alkhouri N and Aggarwal P contributed to the drafting and revision of the manuscript; Harrison S and Noureddin M contributed to the revision of the manuscript.
Supported by AHRQ grant, No. R01HS026937 (Le P and Payne J).
Institutional review board statement: This study has been reviewed and approved by the Arizona Liver Health IRB (protocol 2020-ALH-NAFLD-01).
Informed consent statement: As this was a retrospective review from a deidentified patient database, individual informed consent of subject participants was not applicable as per the institutional review board.
Conflict-of-interest statement: There are no potential conflicts (financial, professional, or personal) to disclose by all the authors with respect to data availability, animal research, consent to participate, consent to publish, plant reproducibility, clinical trials registration, author contribution, or conflicts of interest.
Data sharing statement: No additional data available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Naim Alkhouri, MD, Department of Hepatology, Arizona Liver Health, 1601 N Swan Rd, Tucson, AZ 85712, United States. naim.alkhouri@gmail.com
Received: March 7, 2022
Peer-review started: March 7, 2022
First decision: June 8, 2022
Revised: June 30, 2022
Accepted: August 10, 2022
Article in press: August 10, 2022
Published online: August 27, 2022
Processing time: 171 Days and 17 Hours
Abstract
BACKGROUND

There is an urgent need to risk stratify patients with suspected nonalcoholic fatty liver disease (NAFLD) and identify those with fibrotic nonalcoholic steatohepatitis. This study aims to apply a simple diagnostic algorithm to identify subjects with at-risk NAFLD in the general population.

AIM

To apply a simple diagnostic algorithm to identify subjects with at-risk NAFLD in the general population.

METHODS

Adult subjects were included from the National Health and Nutrition Examination Survey database (2017-2018) if they had elevated alanine aminotransferase (ALT) and excluded if they had evidence of viral hepatitis or significant alcohol consumption. A fibrosis-4 (FIB4) cutoff of 1.3 differentiated patients with low risk vs high risk disease. If patients had FIB4 > 1.3, a FAST score < 0.35 ruled out advanced fibrosis. Patients with FAST > 0.35 were referred to a specialist. The same algorithm was applied to subjects with type 2 diabetes mellitus (T2DM).

RESULTS

Three thousand six hundred and sixty-nine patients were identified who met all inclusion and exclusion criteria. From this cohort, 911 (28.6%) patients had elevated ALT of which 236 (22.9%) patients had elevated FIB4 scores ≥ 1.3. Among patients with elevated FIB4 score, 75 (24.4%) had elevated FAST scores, ruling in advanced fibrosis. This accounts for 2.0% of the overall study population. Applying this algorithm to 737 patients with T2DM, 213 (35.4%) patients had elevated ALT, 85 (37.9%) had elevated FIB4, and 42 (46.1%) had elevated FAST scores. This accounts for 5.7% of the population with T2DM.

CONCLUSION

The application of this algorithm to identify at-risk NAFLD patients in need for specialty care is feasible and demonstrates that the vast majority of patients do not need subspecialty referral for NAFLD.

Keywords: Non-alcoholic fatty liver disease; Nonalcoholic steatohepatitis; Hepatology; Diabetes; Endocrinology; Primary care

Core Tip: Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis represent a major public health threat as the incidence and prevalence continues to rise. This patient population has the potential to overwhelm hepatology clinics if not appropriately triaged by those physicians making referrals. This manuscript presents a simple diagnostic algorithm that outlines how physicians can approach an undifferentiated patient with findings concerning for NAFLD.