ReviewOrthopaedic surgery2026
Advances in Gait Alterations and Rehabilitation After Anterior Cruciate Ligament Reconstruction: Biomechanics and Emerging Technologies.
Review in Orthopaedic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Gait asymmetry as a determinant of functional recovery and return to sport after ACL reconstruction: a cross-sectional biomechanical analysis.Frontiers in bioengineering and biotechnology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Anterior cruciate ligament (ACL) injuries are prevalent in sports and daily life, often leading to functional instability and long-term complications such as osteoarthritis. This literature review synthesizes advancements in postoperative gait analysis following ACL reconstruction (ACLR), focusing on biomechanical alterations, rehabilitation outcomes, and emerging technologies. Current methodologies, including three-dimensional motion capture, force plate kinetics, surface electromyography (sEMG), wearable sensors, machine learning and artificial intelligence, reveal persistent kinematic asymmetries, and altered joint loading patterns in ACLR patients. Rehabilitation interventions, such as neuromuscular training, biofeedback, and AI-assisted systems, show promise in restoring dynamic stability but require standardization and cost optimization. Limitations of existing studies include small sample sizes, short follow-up periods, and methodological inconsistencies. Future research should prioritize multicenter longitudinal studies, multimodal data integration, and AI-driven precision rehabilitation to optimize recovery and mitigate long-term risks. This study aims to elucidate the role of gait analysis in optimizing rehabilitation protocols and mitigating long-term complications by evaluating the strengths and limitations of existing approaches.
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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.