Evidence map›Paper›PMID 39702079›Full record

ArticleBMC musculoskeletal disorders2024

Development of a clinical predictive model for cement loosening after vertebral augmentation in osteoporotic vertebral compression fractures.

Qipeng Wei, Jinxiang Zhan, Xiaofeng Chen, Hao Li, Weijun Guo, Zihao Liu, Qingyan Huang, Dongling Cai

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Qipeng WeiDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Jinxiang ZhanGuangzhou University of Chinese Medicine, Guangzhou, China.
Xiaofeng ChenDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Hao LiDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Weijun GuoDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Zihao LiuGuangzhou University of Chinese Medicine, Guangzhou, China.
Qingyan HuangDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Dongling CaiDepartment of Orthopedics, Panyu Hospital of Chinese Medicine, Guangzhou, Guangdong, China. cdl_spine@126.com.

Funding

Panyu District Science and Technology Programme Major Healthcare Projects 2022-Z04-112
6 · The paper itself

Abstract

purposeThis study aims to identify the risk factors associated with bone cement loosening after percutaneous vertebroplasty/kyphoplasty (PVP/PKP) for osteoporotic vertebral compression fractures (OVCF) and to develop a clinical prediction model for bone cement loosening.

methodsClinical data of patients who underwent PVP/PKP for OVCF at Guangzhou Panyu Hospital from June 2017 to June 2021 were collected, with a division into loosening group and normal group based on postoperative follow-up imaging. Univariate analysis was conducted to explore the correlation between clinical data and bone cement loosening. Multivariate logistic regression analysis was performed to identify independent risk factors for bone cement loosening after PVP/PKP for OVCF. The nomogram prediction model was constructed using R and evaluated through DCA, calibration curve, and ROC curve assessments.

results① Multivariate analysis indicated age, time from injury to surgery, bone density, thoracolumbar kyphosis(TLK), anti-osteoporosis therapy, surgical approach, and bone cement shape were independent risk factors for bone cement loosening after PVP/PKP for OVCF. ② The nomogram clinical prediction model based on multivariate regression showed an area under the ROC curve of 0.86. The DCA curve and calibration curve demonstrated good consistency between predicted and actual results.

conclusionThe clinical prediction model for bone cement loosening after PVP/PKP in OVCF indicates that advanced age, longer time from injury to surgery, low bone density, inadequate correction of thoracolumbar kyphosis, PKP, non-anti-osteoporosis therapy, and block-type bone cement are associated with a higher risk of bone cement loosening, showing excellent discriminative capacity and promising clinical utility.

Indexed as

Bone CementsFractures, CompressionNomogramsOsteoporotic FracturesSpinal FracturesVertebroplastyAgedAged, 80 and overFemaleHumansKyphoplastyMaleMiddle AgedPostoperative ComplicationsRetrospective StudiesRisk FactorsBone CementsBone cement looseningOsteoporosisPrediction modelRisk factorsSpinal fractures

Identifiers

PMID39702079
PMCPMC11660886

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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.