Evidence map›Paper›PMID 40679251›Full record

ArticleVeterinary surgery : VS2025

Integrated endoscopic thoracolumbar mini-hemilaminectomy and lateral corpectomy in cadaver dogs.

Megan M Wolfe, Lisa R Bartner, Eric Monnet, Katherine Neal

Abstract read
In one paragraph

Article in Veterinary surgery : VS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Megan M WolfeDepartment of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.ORCID https://orcid.org/0009-0005-9112-458X
Lisa R BartnerDepartment of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.
Eric MonnetDepartment of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.ORCID https://orcid.org/0000-0002-0058-2210
Katherine NealDepartment of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.

Funding

American College of Veterinary Internal Medicine Neurology Holliday Grant
6 · The paper itself

Abstract

objectiveTo evaluate the feasibility of minimally invasive integrated endoscopic mini-hemilaminectomy and thoracolumbar lateral corpectomy at six intervertebral disc spaces in the canine thoracolumbar vertebral column. STUDY

designExperimental, randomized cadaveric study. ANIMALS: Eight cadaver dogs euthanized for reasons unrelated to this study.

methodsPreoperative computed tomography (CT) scans were performed for surgical planning. Using an endoscopic system, mini-hemilaminectomy and thoracolumbar lateral corpectomy were performed from the T11-12 through L3-4 intervertebral disc spaces, with cadavers in sternal recumbency or positioned at a 30°-60° angle. Postoperative CT scans were used to measure corpectomy dimensions as a percentage of total vertebral dimensions.

resultsMedian ± interquartile range (IQR) corpectomy dimensions were 23.07% ± 16.47% of vertebral body length, 46.76% ± 21.7% of vertebral body height, and 74.44% ± 47.37% of vertebral canal diameter. Targeted dimensions were achieved at all surgical sites from T11-12 through L3-4.

conclusionIntegrated endoscopic thoracolumbar lateral corpectomy was successfully performed at all intervertebral disc spaces from T11-12 through L3-4 using an endoscopic system, although thoracic sites required more practice. CLINICAL SIGNIFICANCE: This pilot study will guide further clinical applications of minimally invasive neurosurgery in small animal patients.

Indexed as

EndoscopyLaminectomyLumbar VertebraeThoracic VertebraeAnimalsCadaverDogsIntervertebral DiscTomography, X-Ray Computed

Identifiers

PMID40679251
PMCPMC12618160

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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.