Evidence map›Paper›PMID 39087185›Full record

ArticleCureus2024

Quantitative Assessment of Intervertebral Disc Degeneration Using the Disc Signal Intensity Index in Patients With Spine-Related Pain.

Koki Tsuchiya, Ichiro Okano, Reon Kobayashi, Yusuke Dodo, Joji Ogawa, Eiko Hara, Asae Taketomi, Yoshifumi Kudo

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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

8 authors.

Koki TsuchiyaDepartment of Orthopedic Surgery, Showa University School of Medicine, Tokyo, JPN.
Ichiro OkanoDepartment of Orthopedic Surgery, Showa University School of Medicine, Tokyo, JPN.
Reon KobayashiDepartment of Anesthesiology, Showa University School of Medicine, Tokyo, JPN.
Yusuke DodoDepartment of Orthopedic Surgery, Showa University School of Medicine, Tokyo, JPN.
Joji OgawaDepartment of Orthopedic Surgery, Showa University School of Medicine, Tokyo, JPN.
Eiko HaraDepartment of Anesthesiology, Showa University School of Medicine, Tokyo, JPN.
Asae TaketomiDepartment of Anesthesiology, Showa University School of Medicine, Tokyo, JPN.
Yoshifumi KudoDepartment of Orthopedic Surgery, Showa University School of Medicine, Tokyo, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective This is a retrospective observational study that aims to investigate the association between disc signal intensity index (DSI2) scores and patient-reported outcome measures in patients with lumbar spine disorders. Methods We introduced DSI2 to quantitatively assess disc degeneration. MRI records of patients with lumbar spine-related pain between 2019 and 2022 were analyzed retrospectively. Patient demographics and outcomes were collected, including the Numerical Rating Scale of Pain and EuroQol Group 5 Dimension 5-Level Quality of Life (EQ-5D-5L) scores. The DSI2 was calculated by dividing the mean signal intensity of the L1-S1 discs by that of the CSF on midsagittal T2-weighted MRI images. Results Each DSI2 level corresponded to a Pfirrmann grade score at the respective lumbar level. Multivariable linear regression analysis using the EQ-5D-5L as the objective variable identified BMI (p = 0.007) and average DSI2 (p = 0.018) as independent risk factors for EQ-5D-5L deterioration. However, the mean Pfirrmann grade score was not an independent risk factor (p = 0.58). Conclusion Our study using DSI2 showed the relationship between disc degeneration and EQ-5D-5L deterioration. Distinct from the Pfirrmann grading system, the DSI2 method is a promising alternative for future disc research that excellently detects the subtle progression of degeneration.

Indexed as

disc signal intensity indexeuroqol group 5 dimension 5-level quality of lifei̇ntervertebral disc degenerationquality of lifespine-related pain

Identifiers

PMID39087185
PMCPMC11290383

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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.