ArticleFrontiers in bioengineering and biotechnology2025
Comparison of robotic AI-assisted and manual pedicle screw fixation for treating thoracolumbar fractures: a retrospective controlled trial.
Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses 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
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy and clinical outcomes of TiRobot-assisted pedicle screw fixation for thoracolumbar fractures: a meta-analysis.Journal of robotic surgery · 2026Pooled it
- The rise of robotics and AI-assisted surgery in modern healthcare.Journal of robotic surgery · 2025Pooled it
- Application of a posture-sensing method combined with blind guidewire probing in percutaneous pedicle screw placement for single-level thoracolumbar compression fractures: a retrospective comparative study.Journal of orthopaedic surgery and research · 2026Article
- Artificial intelligence in modern clinical practice (Review).Medicine internationalReview
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To compare the clinical efficacy and screw placement accuracy of robot artificial intelligence (AI)-assisted percutaneous screw fixation and conventional C-arm-assisted percutaneous screw fixation (manual placement) in the treatment of thoracolumbar single-segment fractures without neurological symptoms. Methods: This study is a single-center retrospective analysis involving patients with thoracolumbar single-segment fractures without neurological symptoms. Patients were divided into Group A (robotic AI-assisted placement) and Group B (manual placement). Clinical outcomes such as operative time, intraoperative fluoroscopy frequency, screw placement accuracy, postoperative complications, length of hospital stay, and postoperative pain were compared between the two groups. Results: Group A showed significantly better screw placement accuracy, fewer intraoperative fluoroscopy attempts, shorter fluoroscopy time, and fewer guidewire adjustments compared to Group B (P < 0.05). Additionally, Group A had shorter hospital stays, a lower incidence of postoperative complications, and short-term greater improvement in Visual Analog Scale (VAS) scores (P < 0.05). However, after 1 year of follow-up, there was no statistically significant difference between the two groups in the improvement of VAS scores. Conclusion: Robotic AI-assisted placement improves pedicle screw placement accuracy, reduces intraoperative fluoroscopy frequency and time, alleviates postoperative pain, and accelerates patient recovery. This approach aligns with the principles of enhanced recovery in orthopedic surgery and holds promise for wider clinical application in the treatment of thoracolumbar fractures.
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