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
Core Tip

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.