Evidence map›Paper›PMID 40004663›Full record

ReviewJournal of clinical medicine2025

Optimizing Single-Position Prone Lateral Lumbar Interbody Fusion with Exoscopic Technology: A Review of Key Innovations.

Christian Quinones, John Preston Wilson, Deepak Kumbhare, Bharat Guthikonda, Stanley Hoang

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 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

5 authors.

Christian QuinonesDepartment of Neurosurgery, Louisiana State University Health Shreveport, Shreveport, LA 71103, USA.
John Preston WilsonDepartment of Neurosurgery, Louisiana State University Health Shreveport, Shreveport, LA 71103, USA.ORCID 0000-0002-3846-3188
Deepak KumbhareDepartment of Neurosurgery, Louisiana State University Health Shreveport, Shreveport, LA 71103, USA.
Bharat GuthikondaDepartment of Neurosurgery, Louisiana State University Health Shreveport, Shreveport, LA 71103, USA.
Stanley HoangDepartment of Neurosurgery, Louisiana State University Health Shreveport, Shreveport, LA 71103, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Minimally invasive spine surgery has advanced significantly over the past decade, integrating technologies such as intraoperative navigation, robotics, and artificial intelligence with innovative techniques such as single-position prone lateral transpsoas lumbar interbody fusion (proLIF). While proLIF offers excellent clinical outcomes for a wide range of lumbar pathologies, the lateral approach to lumbar spine presents technical and ergonomic challenges, including an increased need for soft-tissue dissection and unfavorable ergonomics for surgeons. This review details how the combination of emerging technologies has been applied in minimally invasive lumbar spine surgery. It also describes the novel application of an exoscope during navigation-guided proLIF. The benefits offered by the exoscope included high-resolution, three-dimensional visualization, enhanced maneuverability, and improved surgeon ergonomics. By combining emerging technologies with novel surgical approaches, this review demonstrates the recent advancements in minimally invasive spine surgery and underscores the exoscope's potential to enhance visualization and optimize ergonomics for surgeons.

Indexed as

interbody fusionlaterallumbar stenosisminimally invasive spine surgery (MISS)prone transpsoassingle-position surgeryspinal fusiontranspsoas

Identifiers

PMID40004663
PMCPMC11856252

What OpenQuestion holds

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Registered trials

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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.