ArticleFrontiers in pain research (Lausanne, Switzerland)2023
Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment.
Article in Frontiers in pain research (Lausanne, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025Pooled it
- Factors associated with work-related musculoskeletal disorders using machine learning approaches: a systematic review.Annals of occupational and environmental medicine · 2026Review
- Explainable AI reveals tissue pathology and psychosocial drivers of opioid prescription for non-specific chronic low back pain.Scientific reports · 2025Article
- Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Review
- Machine Learning Clinical Decision Support for Interdisciplinary Multimodal Chronic Musculoskeletal Pain Treatment: Prospective Pilot Study of Patient Assessment and Prognostic Profile Validation.JMIR rehabilitation and assistive technologies · 2025Article
- Article
- Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool.JMIR medical informatics · 2024Article
- Applying AI to Safely and Effectively Scale Care to Address Chronic MSK Conditions.Journal of clinical medicine · 2024Article
- Pain Research and Treatment: Policy Implications.Policy insights from the behavioral and brain sciences · 2024Article
- Clinical prediction model for interdisciplinary biopsychosocial rehabilitation in osteoarthritis patients.European journal of physical and rehabilitation medicine · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Chronic musculoskeletal pain is a prevalent condition impacting around 20% of people globally; resulting in patients living with pain, fatigue, restricted social and employment capacity, and reduced quality of life. Interdisciplinary multimodal pain treatment programs have been shown to provide positive outcomes by supporting patients modify their behavior and improve pain management through focusing attention on specific patient valued goals rather than fighting pain. Methods: Given the complex nature of chronic pain there is no single clinical measure to assess outcomes from multimodal pain programs. Using Centre for Integral Rehabilitation data from 2019-2021 ( Results: Individual algorithm performance ranged from 0.49 to 0.65 AUC reflecting characteristic outcome variation across patients, and unbalanced training data with high positive proportions of up to 86% for some measures. As expected, no single outcome provided a reliable indicator, however the complete set of algorithms established a stratified prognostic patient profile. Patient level validation achieved consistent prognostic assessment of outcomes for 75.3% of the study group ( Discussion: These results indicate that although no single algorithm was individually conclusive, the complete stratified profile consistently identified patient outcomes. Our predictive profile provides promising positive contribution for clinicians and patients to assist with personalized assessment and goal setting, program engagement and improved patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.