ArticleNorth American Spine Society journal2022
Radiographic analysis of neuroforaminal and central canal decompression following lateral lumbar interbody fusion.
Article in North American Spine Society journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Multilevel Lateral Lumbar Interbody Fusion for Symptomatic Spondylotic Stenosis and Severe Disc Degeneration Without Scoliosis: Single-Institutional Case Series and Lessons Learned.International journal of spine surgery · 2026Article
- A CT-based radiographic analysis of parameters of congenital lumbar neuroforaminal stenosis.Journal of spine surgery (Hong Kong) · 2025Article
- An optimal disc height changes for successful indirect decompression with OLIF.Scientific reports · 2025Article
- Efficacy of OLIF combined with pedicle screw internal fixation for lumbar spinal stenosis on spinal canal changes before and after surgery.Journal of orthopaedic surgery and research · 2023Article
- Commentary on "Radiographic analysis of neuroforaminal and central canal decompression following lateral lumbar interbody fusion".North American Spine Society journal · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lateral lumbar interbody fusion (LLIF) is a minimally invasive surgical option for treating symptomatic degenerative lumbar spinal stenosis (DLSS) in select patients. However, the efficacy of LLIF for indirectly decompressing the lumbar spine in DLSS, as well as the best radiographic metrics for evaluating such changes, are incompletely understood. Methods: A single-institutional cohort of patients who underwent LLIF for DLSS between 5/2015 - 12/2019 was retrospectively reviewed. Diameter, area, and stenosis grades were measured for the central canal (CC) and neural foramina (NF) at each LLIF level based on preoperative and postoperative T2-weighted MRI. Baseline facet joint (FJ) space, degree of FJ osteoarthritis, presence of spondylolisthesis, interbody graft position, and posterior disc height were analyzed as potential predictors of radiographic outcomes. Changes to all metrics after LLIF were analyzed and compared across lumbar levels. Preoperative and intraoperative predictors of decompression were then assessed using multivariate linear regression. Results: A total of 102 patients comprising 153 fused levels were analyzed. Pairwise linear regression of stenosis grade to diameter and area revealed significant correlations for both the CC and NF. All metrics except CC area were significantly improved after LLIF ( Conclusions: Radiographically, LLIF is effective at indirect compression of the CC and NF at all lumbar levels, though worse FJ osteoarthritis predicted higher degrees of post-operative stenosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.