Evidence map›Paper›PMID 39882465›Full record

ArticleHeliyon2025

Transforaminal lumbar interbody fusion (TLIF) surgery: A finite element analysis of open and minimally invasive approach on L4-L5 segment.

Kishore Pradeep, Bidyut Pal, Kaushik Mukherjee, Gautam M Shetty

Abstract read
In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Kishore PradeepDepartment of Mechanical Engineering, Indian Institute of Engineering Science and Technology (IIEST), Shibpur, Howrah, 711103, West Bengal, India.
Bidyut PalDepartment of Mechanical Engineering, Indian Institute of Engineering Science and Technology (IIEST), Shibpur, Howrah, 711103, West Bengal, India.
Kaushik MukherjeeDepartment of Mechanical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110 016, India.
Gautam M ShettyQI Spine Clinic, Mumbai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To compare the effect of minimally invasive and open transforaminal lumbar interbody fusion (TLIF) approaches in fusing the L4-L5 segment and predicting the potential risk of adjacent segment degeneration (ASD). Methods: A computed tomography scan image was processed and the three-dimensional model of the L1-L5 spine was reconstructed. The minimally invasive and Open TLIF finite element models were constructed. The models were analyzed using an axial compressive load (500 N) and physiological movements like flexion, extension, and lateral bending with a combined load and moment (150 N and 10 Nm). The ranges of motion (ROM), stress-strain distributions on the L4-L5 implanted segment and cranial adjacent soft structures were compared with the intact model. Results: A substantially comparable drop in ROM was observed for both models due to implantation. The stress and strain distributions on the implanted segment of both models were nearly identical. The peak strain on the L4-L5 was higher than 0.007 for both models. The maximum stress and strain observed on adjacent segment soft structures, except for the annulus fibrosus of both the implanted models, were substantially higher than the intact structures. Conclusions: The open and MI-TLIF approaches are effective in reducing ROMs. However, the higher stress and strain on the L4-L5 segment indicate the chances of bone failure. The higher stress and strain on the adjacent segment soft structures indicate the potential risk of ASD in both models. However, considering the lower intrusive nature of the MI-TLIF technique, it might be favoured over Open TLIF.

Indexed as

Adjacent segment degenerationDegenerative Disc DiseasesFinite element analysisLumbar spineTransforaminal lumbar interbody fusion

Identifiers

PMID39882465
PMCPMC11774785

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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.