Evidence map›Paper›PMID 42310161›Full record

ReviewEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026

Role of paraspinal muscle fatty infiltration in predicting adjacent segment disease after lumbar spinal fusion: a systematic review and meta-analysis.

Tan Lam Minh Nguyen, Hsuan-Tung Lee, Yu-Chi Hsu, Tan Thanh Nguyen, Duy Nguyen Anh Tran, Serena Hu, Jason Pui-Yin Cheung, Klaus John Schnake, Wongthawat Liawrungrueang, Takaki Yoshimizu and 6 more

Abstract readReview
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In one paragraph

Review in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 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

16 authors.

Tan Lam Minh Nguyen *International Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.ORCID http://orcid.org/0009-0006-9794-8552
Hsuan-Tung Lee *School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.ORCID http://orcid.org/0000-0003-1069-4563
Yu-Chi Hsu *School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Tan Thanh NguyenDepartment of Orthopedics, Faculty of Medicine, Can Tho University of Medicine and Pharmacy, Can Tho, Vietnam.
Duy Nguyen Anh TranDepartment of Orthopedics, Faculty of Medicine, Can Tho University of Medicine and Pharmacy, Can Tho, Vietnam.
Serena HuSchool of Medicine, Stanford University, Redwood City, USA.
Jason Pui-Yin CheungDepartment of Orthopaedics and Traumatology, University of Hong Kong, Hong Kong, China.
Klaus John SchnakeCenter for Spinal and Scoliosis Surgery, Malteser Waldkrankenhaus Erlangen, Erlangen, Germany.
Wongthawat LiawrungrueangDepartment of Orthopaedics, School of Medicine, University of Phayao, Phayao, Thailand.
Takaki YoshimizuDepartment of Orthopedic Surgery, Seirei Hamamatsu General Hospital, Hamamatsu, Japan.
Daisuke SakaiDepartment of Orthopaedic Surgery, Surgical Science, Tokai University School of Medicine, Kanagawa, Japan.
Jason C HsuProgram in Biotech and Healthcare Management, Taipei Medical University, Taipei, Taiwan.
Hsin-Lun LeeDepartment of Radiology, Taipei Medical University Hospital, Taipei, Taiwan.
Sung Huang Laurent TsaiDepartment of Orthopedics, Taipei Medical University Hospital, Taipei, Taiwan.
Khanh Nguyen Quoc LeIn-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. khanhlee@tmu.edu.tw.
Meng-Huang WuDepartment of Orthopedics, Taipei Medical University Hospital, Taipei, Taiwan. maxwutmu@gmail.com.

Funding

Intelligent Spinal Protection Tension System Q3101
6 · The paper itself

Abstract

purposeTo evaluate whether preoperative fat infiltration (FI) in paraspinal muscles (PSM), specifically the multifidus (MF) and erector spinae (ES), is a reliable predictor of adjacent segment disease (ASD) after lumbar spinal fusion in adults.

methodsA systematic review and meta-analysis was conducted by searching PubMed, Embase, and Scopus from inception to March 2025. Studies with cohort or case-control designs reporting on preoperative FI and ASD development were included. Of 630 studies, 11 met the eligibility criteria, involving 1,474 patients, and were analyzed. Mean differences were pooled using a random-effects model.

resultsPooled analysis showed that preoperative FI was significantly higher in the ASD development group (MD = 4.83%; 95% CI: 3.28 to 6.39; I² = 59.0%). Patients in the ASD group were significantly older compared to controls (MD = 1.88 years; 95% CI: 0.89 to 2.86). Subgroup analysis by fusion length (short vs. long) and muscle type (MF vs. PSM) revealed no significant differences in effect sizes, indicating the consistent predictive value of FI across groups. Meta-regression analyses indicated that fusion length and patient age did not significantly moderate the association between FI and ASD, suggesting that FI is an independent predictor regardless of these demographic and surgical factors.

conclusionPreoperative PSM FI is associated with increased ASD risk after LSF. Incorporating FI assessment into preoperative surgical planning may help optimize outcomes, while targeted preoperative muscle optimization could offer a promising strategy to improve long-term results.

Indexed as

Adjacent segment diseaseErector spinaeFatty infiltrationLumbar spinal fusionMultifidusParaspinal muscles

Identifiers

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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.