Evidence map›Paper›PMID 39654076›Full record

ArticleAsian spine journal2024

Validation of the visual body image classification in adolescent idiopathic scoliosis: a retrospective study.

Han Sol Kim, Jae Yoon Jeong, Yoon Jae Cho, Tae Sik Goh, Jung Sub Lee

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Article in Asian spine journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Han Sol KimDepartment of Orthopaedic Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University, Busan, Korea.
Jae Yoon JeongDepartment of Orthopaedic Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University, Busan, Korea.
Yoon Jae ChoDepartment of Orthopaedic Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University, Busan, Korea.
Tae Sik GohDepartment of Orthopaedic Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University, Busan, Korea.
Jung Sub LeeDepartment of Orthopaedic Surgery, Biomedical Research Institute, Pusan National University Hospital, Pusan National University, Busan, Korea.

Funding

Pusan National University
6 · The paper itself

Abstract

STUDY

designA prospective study. PURPOSE: To diagnose scoliosis, a visit to the hospital for radiography is typically necessary. In such cases, children with scoliosis are exposed to radiation, which may place their health at risk. Therefore, we sought to determine whether a classification method based on visual body images obtained through photography can be used to diagnose scoliosis. OVERVIEW OF LITERATURE: Scoliosis can be diagnosed and classified into various types using radiographs. However, no studies have attempted to classify scoliosis based on visual body images.

methodsFrom January 1, 2019 to December 31, 2022, 136 patients newly diagnosed with Adolescent idiopathic scoliosis and 124 healthy candidates from our institution were enrolled. This study classified body images into five types based on visual confirmation of the positional relationship of the body. The accuracy of this classification method was identified by calculating its sensitivity, specificity, and reproducibility of this classification method within and between observers according to kappa value.

resultsOverall, 136 patients and 124 control subjects who visited the Pusan National University Hospital, Busan, Korea were photographed and compared by obtaining back images and X-ray radiographs. The sensitivity and specificity of the classification method showed a satisfactory-to-good degree of accuracy, although the degree varies depending on the visual body image type. The classification methods exhibited good intraobserver reliability (κ=0.855) and moderate interobserver reliability (κ=0.751).

conclusionsOur classification method showed a high degree of sensitivity and specificity (98.1% sensitivity, 98.9% specificity, and 98.4% accuracy) while exhibiting high reproducibility and ease of access. Based on our findings, we believe that our classification method can be used for scoliosis screening.

Indexed as

Adolescent idiopathic scoliosisValidationVisual body image

Identifiers

PMID39654076
PMCPMC11711174

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