Evidence map›Paper›PMID 42475751›Full record

ArticleJournal of neurosurgery. Case lessons2026

Single-position robot-assisted lateral lumbar corpectomy with minimally invasive posterior spinal fusion for traumatic burst fracture showing MRI-demonstrated indirect decompression: illustrative case.

Ryan S Beyer, Genevieve M Fraipont, Zach Pennington, Luis Daniel Diaz-Aguilar, Martin H Pham

Abstract read
In one paragraph

Article in Journal of neurosurgery. Case lessons, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Ryan S BeyerDepartment of Orthopaedic Surgery, University of California, Irvine, Orange, California.
Genevieve M FraipontUniversity of Southern California Keck School of Medicine, Los Angeles, California.ORCID 0009-0004-5664-2720
Zach PenningtonDepartment of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0001-8012-860X
Luis Daniel Diaz-AguilarDepartment of Neurosurgery, University of California, San Diego School of Medicine, San Diego, California.
Martin H PhamDepartment of Neurosurgery, University of California, San Diego School of Medicine, San Diego, California.ORCID 0000-0002-7733-8902

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLigamentotaxis-based indirect decompression using lateral approaches is well described for degenerative lumbar disease, yet its application in managing burst fractures remains underexplored. OBSERVATIONS: A 72-year-old osteopenic male with an L4 burst fracture underwent a single-position robot-assisted lateral L4 corpectomy, L2-3 oblique lumbar interbody fusion, L5-S1 lateral anterior lumbar interbody fusion, and robot-assisted percutaneous segmental fixation from L2 to the ilium. Postoperative MRI demonstrated significant indirect decompression with a decrease in ligamentous buckling and restoration of the spinal canal cross-sectional area. The ligamentotaxis created by the height and lordosis restoration produced adequate decompression without resection of the ventral retropulsed fragments or posterior direct decompression. LESSONS: This case illustrates that single-position lateral lumbar corpectomy can achieve indirect decompression while sparing the morbidity of an open posterior approach. To the authors' knowledge, this is the first report with MRI evidence of indirect decompression following single-position lateral lumbar corpectomy. https://thejns.org/doi/10.3171/CASE26118.

Indexed as

case reportindirect decompressionlateral lumbar corpectomynavigationroboticssingle-position surgery

Identifiers

PMID42475751
PMCPMC13383589

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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.