Noda Mitsuaki, Takahara Shunsuke, Inui Atsuyuki, Oe Keisuke, Osawa Shin, Matsushita Takehiko
Orthopedics, Nishi Hospital, Kobe, JPN.
Department of Orthopedics, Hyogo Prefectural Kakogawa Medical Center, Kakogawa, JPN.
Cureus. 2023 Dec 30;15(12):e51363. doi: 10.7759/cureus.51363. eCollection 2023 Dec.
Introduction We introduced a novel numerical index known as posterior protrusion measures (PPM), derived from lateral plain radiograph images, which effectively serves to distinguish stable from unstable pertrochanteric fractures. The present study aims to scrutinize PPM values among two classified fracture patterns, stable and unstable, within the three-dimensional (3D) CT classification system, establishing a numeric threshold for PPM to differentiate between these groups; explore the potential relationship between the PPM index and unclassified categories; investigate how groups divided by the PPM threshold value can predict fracture stability based on 3D CT. Materials and methods In this study, three observers were tasked with measuring PPM on a single occasion. The chi-square test assessed the association between each demographic parameter on a categorical scale and stable/unstable groups. Continuous variables were also subject to examination. Receiver operating characteristic (ROC) analysis was employed to determine optimal cut-off points of PPM for predicting the presence of stable versus unstable groups. Additionally, the chi-square test examined the linear relation between separated groups based on the defined threshold PPM value and the stable/unstable groups. Results A total of 106 pertrochanteric fractures were identified using CT scan images and plain radiographs in the 3D CT classification system, revealing the stable group of 35 patients and the unstable group of 71 patients. The PPM values for stable/unstable fractures were, on average (± standard deviation), 0.34±0.25/0.50±0.29 for observer 1, 0.31±0.23/0.57±0.31 for observer 2, and 0.41±0.29/0.57±0.26 for observer 3, respectively (p<0.01). We established 0.3 as the cut-off value for PPM. The average PPM value among three observers represented each patient to assess fracture stability. The group with PPM <0.3 included 27 patients (16 stable and 11 unstable), and the group with PPM ≥0.3 group comprised 79 patients (19 stable and 60 unstable; p<0.005). Conclusion The present study revealed a significant difference in PPM values among stable and unstable 3D CT classification groups. Additionally, a threshold PPM value of 0.3 suggests a pivotal point for differentiating fracture stability. This innovative methodology makes a substantial contribution to clinical endeavors, potentially circumventing the necessity for 3D CT scanning.
引言 我们引入了一种名为后凸测量值(PPM)的新型数值指标,该指标源自髋关节侧位平片图像,可有效区分稳定型与不稳定型股骨转子间骨折。本研究旨在审视三维(3D)CT分类系统中稳定型和不稳定型这两种分类骨折模式的PPM值,确定区分这两组的PPM数值阈值;探索PPM指标与未分类类别之间的潜在关系;研究基于PPM阈值划分的组别如何根据3D CT预测骨折稳定性。材料与方法 在本研究中,三名观察者负责单次测量PPM。卡方检验评估了分类量表上每个人口统计学参数与稳定/不稳定组之间的关联。连续变量也进行了检验。采用受试者工作特征(ROC)分析来确定预测稳定组与不稳定组存在的PPM最佳截断点。此外,卡方检验考察了基于定义的PPM阈值划分的组别与稳定/不稳定组之间的线性关系。结果 在3D CT分类系统中,通过CT扫描图像和平片共识别出106例股骨转子间骨折,其中稳定组35例,不稳定组71例。观察者1测得的稳定/不稳定骨折的PPM值平均(±标准差)分别为0.34±0.25/0.50±0.29,观察者2为0.31±0.23/0.57±0.31,观察者3为0.41±0.29/0.57±0.26(p<0.01)。我们确定PPM的截断值为0.3。三名观察者的平均PPM值代表每位患者以评估骨折稳定性。PPM<0.3的组包括27例患者(16例稳定,11例不稳定),PPM≥0.3的组包括79例患者(19例稳定,60例不稳定;p<0.005)。结论 本研究揭示了3D CT分类的稳定组和不稳定组之间PPM值存在显著差异。此外,PPM阈值0.3表明是区分骨折稳定性的关键点。这种创新方法对临床工作有重大贡献,可能无需进行3D CT扫描。