Evidence map›Paper›PMID 41695907›Full record

ReviewSpine surgery and related research2026

An Evaluation of Lumbar Foraminal Stenosis Radiologic Grading Systems: A Systematic Review.

Laura C M Ndjonko, Nikol N Kralimarkova, Yashoswini Chakraborty, Zayn S Bajwa, Jasmine X Zimmer, Ayomikun A Taiwo, Imani N Bah, Sami S Khan, Eric K Holder

Abstract readReview
In one paragraph

Review in Spine surgery and related research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

9 authors.

Laura C M NdjonkoNorthwestern University, Evanston, Illinois, USA.
Nikol N KralimarkovaSwansea University Medical School, Institute of Life Science 2, Sketty, Swansea, UK.
Yashoswini ChakrabortyNorthwestern University, Evanston, Illinois, USA.
Zayn S BajwaNorthwestern University, Evanston, Illinois, USA.
Jasmine X ZimmerNorthwestern University, Evanston, Illinois, USA.
Ayomikun A TaiwoNorthwestern University, Evanston, Illinois, USA.
Imani N BahStritch School of Medicine, Maywood, Illinois, USA.
Sami S KhanNorthwestern University, Evanston, Illinois, USA.
Eric K HolderYale Department of Orthopaedics & Rehabilitation, New Haven, Connecticut, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Symptomatic lumbar foraminal stenosis (LFS) occurs when the neuroforamen narrows, compressing the exiting spinal nerve, leading to symptoms such as radicular pain, paresthesias, and potentially weakness. Although cross-sectional imaging studies are used for diagnostic purposes, there is no clear consensus as to which grading system best evaluates LFS, predisposing to inconsistencies in care. This systematic review aimed to evaluate and compare existing published grading systems for LFS to identify (1) systems most used within the literature and (2) the most effective and reliable method for classifying anatomic severity and clinical symptom correlation. Methods: This study is a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, analyzing available literature on grading systems for LFS, level of evidence IV. A comprehensive search of PubMed, Embase, and Cochrane Trials was conducted from inception through July 2024. Eligible studies were evaluated for methods, bias, sample size, patient demographics, imaging modalities, and grading systems. Bias was assessed using the Methodological Index for Non-Randomized Studies. Data were synthesized narratively and descriptively. Results: The review included 35 studies, most using magnetic resonance imaging (88.6%). Seven grading systems have been identified. The original Lee et al. grading system was the most frequently used LFS grading system (69%), followed by Wildermuth et al. (14.3%). Notably, artificial intelligence (AI) grading systems were included in two studies (5.7%). Findings regarding symptom correlation were mixed. Conclusions: The Lee et al. grading system remains the most used grading system for LFS in the literature and is reliable. Several small studies found an association between the Lee et al. system and clinical symptoms/treatment outcomes; however, this was not universally found. Further investigation is needed to validate the newer grading. The introduction of AI may offer promise for refining the diagnostic and clinical utility of published LFS grading systems.

Indexed as

cross-sectional imaginggrading systemsLee et al.lumbar foraminal stenosissystematic review

Identifiers

PMID41695907
PMCPMC12902212

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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.