Evidence map›Paper›PMID 35711699›Full record

ArticleFrontiers in surgery2022

Efficacy of the Dynesys Hybrid Surgery for Patients with Multi-Segmental Lumbar Spinal Stenosis.

Xiao Xiao, Gaoyang Chen, Song Wang, Junliang Liu, Erhu Lin, Ke Chen, Yucheng Xiang, Ke Zhan, Congcong Liu, Zhengbin Yuan and 5 more

Abstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Xiao XiaoDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Gaoyang ChenDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Song WangDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Junliang LiuDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Erhu LinDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Ke ChenDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Yucheng XiangDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Ke ZhanDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Congcong LiuDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Zhengbin YuanDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Minjie YangDepartment of Radiology, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Shuyuan ZhongDepartment of Radiology, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Wanxin ZhenDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Dazhi YangDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.
Songlin PengDepartment of Spine Surgery, The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The efficacy of hybrid (Dynesys and fusion) surgery and the traditional transforaminal lumbar interbody fusion surgery was compared in patients with multi-segmental lumbar spinal stenosis. Methods: A total of 68 patients with multi-segmental lumbar spinal stenosis subjected to surgery were recruited between January 2013 and October 2020 in the First Affiliated Hospital of Southern University of Science and Technology. The patients were divided into a hybrid group ( Results: A statistically significant difference in the duration of surgery was noted between the two groups. After 12 months of follow-up, the range of motion disappeared in the TLIF group, while 63.53% was preserved in the hybrid group with statistically significant differences. A statistically significant difference was identified in the Oswestry Disability Index one week after surgery. Nonetheless, no statistically significant differences were observed at the 12-month post-surgical follow-up. Pfirrmann grade showed a 3.03% upper adjacent segment degeneration rate in the hybrid group (1/33) at 12-month follow-up and 2.86% (1/35) in the TLIF group. Notably, no early complications (screw loosening and wound infection) were identified in the two groups. Conclusion: The Dynesys hybrid surgery combined the advantages of two systems of dynamic stabilization and rigid fusion. Besides, hybrid surgery is potentially a novel approach for the treatment of multi-segmental lumbar spinal stenosis.

Indexed as

dynamic internal fixationhybrid surgerylumbar spinal stenosisspinal fusionthe Dynesys system

Identifiers

PMID35711699
PMCPMC9195297

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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.