Literature DB >> 33280893

Classification of femur trochanteric fracture: Evaluating the reliability of Tang classification.

Bo Yin1, Yuanming He1, Dong Wang1, Junlin Zhou2.   

Abstract

INTRODUCTION: Given the drawbacks of a femoral intertrochanteric fracture classification based on 2-dimensional radiographic imaging, an artificial intelligence-based classification system- the Tang classification system-which uses 3-dimensional image analysis, has previously been developed. This study explored the reliability of the Tang classification by comparing the consistency of this classification with the conventional 2-dimensional femoral intertrochanteric fracture classification systems.
METHODS: X-ray and computed tomography (CT) data of 258 patients with femoral intertrochanteric fractures were classified by 6 orthopedic surgeons using the Evans, Jensen, AO/OTA, and Tang classification systems on 2 separate occasions, 1 month apart. Kappa statistics were used to evaluate the inter- and intraobserver differences in classifications.
RESULTS: When the interobserver reliability was based on X-ray image analysis, the Kappa values for the Evans, Jensen, AO/OTA, and Tang classifications were 0.54 ± 0.03 (moderate agreement), 0.53 ± 0.02 (moderate agreement), 0.46 ± 0.02 (moderate agreement), and 0.63 ± 0.02 (substantial agreement), respectively. When the interobserver reliability was based on CT images, the Kappa values of the Evans, Jensen, AO/OTA, and Tang classifications were 0.49 ± 0.03 (moderate agreement), 0.49 ± 0.03 (moderate agreement), 0.44 ± 0.03 (moderate agreement), 0.64 ± 0.02 (substantial agreement), respectively. For X-ray images, the intraobserver Kappa values for the Evans, Jensen, AO/OTA, and Tang classification were 0.53 ± 0.02 (moderate agreement), 0.54 ± 0.03 (moderate agreement), 0.45 ± 0.03 (moderate agreement), and 0.65 ± 0.03 (substantial agreement), respectively. When intraobserver reliability was based on CT images, the Kappa values for the Evans, Jensen, AO/OTA, and Tang classification were 0.52 ± 0.03 (moderate agreement), 0.52 ± 0.02 (moderate agreement), 0.41 ± 0.02 (moderate agreement), and 0.63 ± 0.03(substantial agreement), respectively.
CONCLUSIONS: The current study suggests that the Tang classification system is more reliable than the Evans, Jensen, and AO/OTA classification systems for measuring intertrochanteric fractures of the proximal femur.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Classification; Intertrochanteric fracture; Reliability

Year:  2020        PMID: 33280893     DOI: 10.1016/j.injury.2020.11.031

Source DB:  PubMed          Journal:  Injury        ISSN: 0020-1383            Impact factor:   2.586


  5 in total

1.  Effect of proximal femoral nail antirotation on clinical outcome, inflammatory factors and myocardial injury markers in patients with femoral trochanteric fracture.

Authors:  Kuanglin Li; Huanhong Yang; Zhaobo Jiang; Wei Peng; Xing Zhou
Journal:  Am J Transl Res       Date:  2022-07-15       Impact factor: 3.940

2.  The Effect of Humanized Nursing Intervention Guided by Computed Tomography Images on Elderly Patients Undergoing Anesthesia for Femur Intertrochanteric Fractures under Intelligent Reconstruction Algorithm.

Authors:  Yanfang He; Yufang Li; Rong Zeng; Xiaoyan Zhang
Journal:  Comput Math Methods Med       Date:  2022-05-24       Impact factor: 2.809

3.  Sub-Classification of AO/OTA-2018 Pertrochanteric Fractures Is Associated With Clinical Outcomes After Fixation of Intramedullary Nails.

Authors:  Hui Song; Sun-Jun Hu; Shou-Chao Du; Wen-Feng Xiong; Shi-Min Chang
Journal:  Geriatr Orthop Surg Rehabil       Date:  2021-11-23

4.  Deep Scale-Variant Network for Femur Trochanteric Fracture Classification with HP Loss.

Authors:  Yuxiang Kang; Zhipeng Ren; Yinguang Zhang; Aiming Zhang; Weizhe Xu; Guokai Zhang; Qiang Dong
Journal:  J Healthc Eng       Date:  2022-03-27       Impact factor: 2.682

5.  A sophisticated fracture classification system of the proximal femur trochanteric region (AO/OTA-31A) based on 3D-CT images.

Authors:  Shi-Min Chang; Zhen-Hai Wang; Ke-Wei Tian; Gui-Xin Sun; Xin Wang; Yun-Feng Rui
Journal:  Front Surg       Date:  2022-08-31
  5 in total

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