Evidence map›Paper›PMID 42027866›Full record

ArticleFrontiers in surgery2026

Integrating core muscle morphology into a predictive model for residual back pain after vertebral augmentation.

Mingyang Huang, Genzhong Xu, Ming Luo

Abstract read
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Article in Frontiers in surgery, 2026. 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

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mingyang Huang *Department of Spine Surgery and Musculoskeletal Tumor, Zhongnan Hospital of Wuhan University, Wuhan, China.
Genzhong Xu *Department of Emergency Surgery, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.
Ming LuoDepartment of Spine Surgery and Musculoskeletal Tumor, Zhongnan Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Residual back pain (RBP) after percutaneous vertebral augmentation (PVA) for osteoporotic vertebral compression fractures (OVCF) remains a significant clinical challenge. Traditional prediction models focus primarily on bone mineral density and procedural factors. This study aimed to develop and validate a novel nomogram that incorporates the morphology of core muscles, notably the gluteal muscles, for personalized RBP risk stratification. Methods: In this retrospective study, clinical data from 428 OVCF patients who underwent PVA at two centers were analyzed. Patients were randomly divided into training and validation cohorts (3:1 ratio). Variables included demographics, fracture characteristics, procedural details, and computed tomography-based measurements of the relative cross-sectional area (rCSA) of paravertebral (multifidus, erector spinae, psoas) and pelvic [gluteus maximus (Gmax), gluteus medius (Gmed)] muscles. Least absolute shrinkage and selection operator and multivariate logistic regression were used to select predictors and build a nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis. Results: The overall incidence of RBP was 17.5%. The final model identified eight independent predictors. Alongside established factors like greater fracture burden and lower cement volume, reduced rCSA of the Gmax and Gmed emerged as significant and strong risk factors ( Conclusions: This study presents a practical nomogram that effectively predicts RBP risk after PVA by integrating core muscle morphology, particularly of the gluteal muscles, with conventional clinical variables. The strong association of gluteal muscle size with pain outcomes underscores the importance of a holistic muscle-bone health assessment. This tool aids in preoperative risk stratification, potentially guiding targeted prehabilitation to improve patient outcomes.

Indexed as

gluteal musclesnomogramosteoporotic vertebral compression fracturepercutaneous vertebral augmentationresidual back pain

Identifiers

PMID42027866
PMCPMC13099926

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