Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain

Background: Low back pain (LBP) is a common cause of disability in the United States and contributes to a great economic burden on both the individual and healthcare system level. Previous studies have investigated home-based therapy as an alternative or supplement to clinical care. In a previous st...

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Main Authors: Kenan Alzouhayli, Nathan D. Schilaty, Takashi Nagai, Luca Rigamonti, April L. McPherson, Benjamin Holmes, Nathaniel A. Bates
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Orthopaedic Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2773157X2500044X
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author Kenan Alzouhayli
Nathan D. Schilaty
Takashi Nagai
Luca Rigamonti
April L. McPherson
Benjamin Holmes
Nathaniel A. Bates
author_facet Kenan Alzouhayli
Nathan D. Schilaty
Takashi Nagai
Luca Rigamonti
April L. McPherson
Benjamin Holmes
Nathaniel A. Bates
author_sort Kenan Alzouhayli
collection DOAJ
description Background: Low back pain (LBP) is a common cause of disability in the United States and contributes to a great economic burden on both the individual and healthcare system level. Previous studies have investigated home-based therapy as an alternative or supplement to clinical care. In a previous study, we found comparable positive outcomes in patients who use an artificial-intelligence (AI) device to manage LBP in both home and clinical settings. In this study, we plan to compare long-term outcomes throughout 1-year post-intervention. Methods: This is a randomized clinical trial of 52 subjects. The investigation compared outcomes in LBP patients who used AI-device resistance therapy in either clinical or home settings. Outcomes of interest were pain, functional status, and kinesiophobia. Results: Group (Home vs. Clinic) was significantly associated with all three PRO parameters (PROMIS PI, PROMIS PF, and TSK scores) (P < 0.007). Home subjects, on average, had lower PROMIS PI and TSK scores (P < 0.007) and higher PROMIS PF scores (P < 0.0001); however, these differences were clinically insignificant. Time and the interaction of Time∗Group were not significant factors that affected PRO scores (P > 0.66). Conclusion: Patients who used AI-resistance training in either home or clinical settings had similar improvement by the end of the intervention and maintained this similarity throughout 1 year of follow-up. AI-resistance training has the potential to be a cost-effective supplement to clinical therapy when managing LBP. Irb approval number: 20-007281.
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spelling doaj-art-9b54927e5c274b6ab392ae2d07adcae32025-08-26T04:14:42ZengElsevierJournal of Orthopaedic Reports2773-157X2025-08-014210059210.1016/j.jorep.2025.100592Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back painKenan Alzouhayli0Nathan D. Schilaty1Takashi Nagai2Luca Rigamonti3April L. McPherson4Benjamin Holmes5Nathaniel A. Bates6Department of Orthopaedics, The Ohio State University Wexner Medical Center, Columbus, OH, USADepartment of Neurosurgery &amp; Brain Repair, University of South Florida, Tampa, FL, USA; Center for Neuromusculoskeletal Research, University of South Florida, Tampa, FL, USAUnited States Army Research Institute of Environmental Medicine, Natick, MA, USADepartment of Orthopedic Surgery, Policlinico San Pietro, Ponte San Pietro, ItalyDepartment of Orthopaedics, The Ohio State University Wexner Medical Center, Columbus, OH, USA; Sports Performance and Research Center, Emory University, Atlanta, GA, USASpine Center, Mayo Clinic, Rochester, MN, USADepartment of Orthopaedics, The Ohio State University Wexner Medical Center, Columbus, OH, USA; Division of Sports Medicine, Mayo Clinic, Rochester, MN, USA; Corresponding author. 265 W 11th Ave, Columbus, OH, 43201, USA.Background: Low back pain (LBP) is a common cause of disability in the United States and contributes to a great economic burden on both the individual and healthcare system level. Previous studies have investigated home-based therapy as an alternative or supplement to clinical care. In a previous study, we found comparable positive outcomes in patients who use an artificial-intelligence (AI) device to manage LBP in both home and clinical settings. In this study, we plan to compare long-term outcomes throughout 1-year post-intervention. Methods: This is a randomized clinical trial of 52 subjects. The investigation compared outcomes in LBP patients who used AI-device resistance therapy in either clinical or home settings. Outcomes of interest were pain, functional status, and kinesiophobia. Results: Group (Home vs. Clinic) was significantly associated with all three PRO parameters (PROMIS PI, PROMIS PF, and TSK scores) (P < 0.007). Home subjects, on average, had lower PROMIS PI and TSK scores (P < 0.007) and higher PROMIS PF scores (P < 0.0001); however, these differences were clinically insignificant. Time and the interaction of Time∗Group were not significant factors that affected PRO scores (P > 0.66). Conclusion: Patients who used AI-resistance training in either home or clinical settings had similar improvement by the end of the intervention and maintained this similarity throughout 1 year of follow-up. AI-resistance training has the potential to be a cost-effective supplement to clinical therapy when managing LBP. Irb approval number: 20-007281.http://www.sciencedirect.com/science/article/pii/S2773157X2500044XLow back painArtificial intelligenceBiomechanicsExercise therapyLongitudinal
spellingShingle Kenan Alzouhayli
Nathan D. Schilaty
Takashi Nagai
Luca Rigamonti
April L. McPherson
Benjamin Holmes
Nathaniel A. Bates
Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
Journal of Orthopaedic Reports
Low back pain
Artificial intelligence
Biomechanics
Exercise therapy
Longitudinal
title Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
title_full Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
title_fullStr Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
title_full_unstemmed Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
title_short Artificial intelligence-guided therapy: Clinic versus home users. Long-term differences in patient-reported outcomes in patients with low back pain
title_sort artificial intelligence guided therapy clinic versus home users long term differences in patient reported outcomes in patients with low back pain
topic Low back pain
Artificial intelligence
Biomechanics
Exercise therapy
Longitudinal
url http://www.sciencedirect.com/science/article/pii/S2773157X2500044X
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