ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025
Identifying gait subgroups in low back pain patients with artificial intelligence: implications for individualized interventions.
Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- AI-Supported Functional Pain Phenotyping in Low Back Pain Using Sensor-Based Gait and Neuromuscular Biomarkers.Sensors (Basel, Switzerland) · 2026Article
- Artificial Intelligence-Based Physical Therapy Interventions for Non-Specific Low Back Pain: A Systematic Review and Meta-Analysis of Randomised Controlled Trials.Journal of clinical medicine · 2026Review
- Bioengineering Support in the Assessment and Rehabilitation of Low Back Pain.Bioengineering (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeThe following study aimed to investigate the existence of different gait profiles in patients with low back pain (LBP) and assess their clinical characteristics.
methodsThis is a cross-sectional retrospective study that included individuals with chronic or acute LBP. Three-dimensional gait kinematics were assessed, including mean angles, range of motion (ROM), and coordination of the trunk and pelvis across three planes. An artificial intelligence algorithm was leveraged to identify distinct gait profiles using principal component analysis, self-organizing maps, and K-means clustering techniques. Clinical characteristics, such as demographics, hip and trunk passive ROM, and hip strength, were compared across profiles using the Kruskal-Wallis test with Bonferroni adjustment at a 5% significance level.
results111 patients were analyzed (mean age 44.6; 56% females). Five distinct gait profiles were identified. Profile 1 (Flexed Trunk) was mainly characterized by an increased lateral trunk ROM and flexed trunk (4.1
conclusionEach of the five profiles identified reveals distinct kinematic and physical characteristics, providing meaningful insights into clinical implications, associated pathologies, anatomical structures at risk, and management.
Indexed as
Identifiers
40504238What OpenQuestion holds
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.