ArticleActa ortopedica brasileira2024
COMPARISON OF DYNESYS AND HYBRID SYSTEM FOR MULTI-SEGMENTAL LDD.
Article in Acta ortopedica brasileira, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- [Spontaneous facet joint fusion and stability assessment following isolated posterior internal fixation for lumbar burst fractures].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026Article
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6 authors.
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Abstract
Objective: To compare effectiveness of Dynesys and hybrid system in treating patients with multi-segmental lumbar degenerative disease (LDD). Methods: Patients involved in this retrospective study were divided into Dynesys (n = 22) and Hybrid (n = 13) groups. Clinical outcomes were evaluated using Oswestry Disability Index (ODI), and Visual Analogue Scale (VAS). Radiologic evaluations included X-ray, MRI, and CT. Furthermore, different complications were analyzed. Results: At the last follow-up, ODI and VAS of each group were improved (p < 0.05), and the range of motion (ROM) of operating segments decreased. However, Dynesys group preserved a larger extent of ROM at the final follow-up (p < 0.05). ROM of the upper adjacent segment was increased in both groups (p < 0.05), while the disc heights were decreased at the final follow-up (p < 0.05). Besides, Dynesys group had a more obvious decrease in the disc height of dynamic segments (p < 0.05). No significant difference existed in complications between both groups (p > 0. 05). Conclusion: In our study, similar satisfactory results were obtained in both groups. Both surgical procedures can be employed as effective treatments for middle-aged and physically active patients with multi-segmental LDD.
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