posterior protrusion measures

  • 文章类型: Journal Article
    介绍我们介绍了一种新的数值指标,称为后突测量(PPM),从横向平面射线照片图像中得出,这有效地用于区分稳定和不稳定的股骨转子骨折。本研究旨在仔细检查两种分类断裂模式中的PPM值,稳定和不稳定,在三维(3D)CT分类系统中,建立PPM的数字阈值以区分这些组;探索PPM指数与未分类类别之间的潜在关系;研究按PPM阈值划分的组如何基于3DCT预测骨折稳定性。材料和方法在这项研究中,三名观察员的任务是一次性测量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。连续变量也要接受检查。采用接收器工作特性(ROC)分析来确定PPM的最佳截止点,以预测稳定组与不稳定组的存在。此外,卡方检验基于定义的阈值PPM值检查了分离组与稳定/不稳定组之间的线性关系。结果在3DCT分类系统中使用CT扫描图像和X线平片共识别出106例经股骨转子骨折,揭示了稳定组的35例患者和不稳定组的71例患者。稳定/不稳定骨折的PPM值是,平均值(±标准偏差),观察员1为0.34±0.25/0.50±0.29,观察员2为0.31±0.23/0.57±0.31,观察员3为0.41±0.29/0.57±0.26(p<0.01)。我们建立了0.3作为PPM的截止值。三个观察者之间的平均PPM值代表每个患者评估骨折稳定性。PPM<0.3组包括27例患者(稳定16例,不稳定11例),PPM≥0.3组包括79例患者(稳定19例,不稳定60例;p<0.005)。结论本研究显示,在稳定和不稳定的3DCT分类组中,PPM值存在显着差异。此外,0.3的阈值PPM值表明了区分骨折稳定性的关键点。这种创新的方法为临床工作做出了重大贡献,潜在地规避了3DCT扫描的必要性。
    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.
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  • 文章类型: Journal Article
    引言缺乏将股骨粗隆部骨折分为稳定或不稳定的精确骨折分类系统,这对医疗保健造成了负担,并具有若干重大影响。我们提出了一种创新的图形索引,我们称之为后突测量(PPM),使用经修订的AO基金会(ArbeitsgemeinschaftfürFosteosynthesisfragen)/骨科创伤协会(AO/OTA)分类系统的平面侧视图射线照相图像。本研究旨在:(i)介绍在修订的AO/OTA分类系统下使用PPM将骨折分类为稳定或不稳定,并设置阈值数值,(Ii)阐明观察者之间和观察者内部协议的可重复性,并研究使用PPM与计算机断层扫描(CT)扫描图像进行骨折分类的一致性。材料和方法从数据库中确定的146名患者中,本研究共纳入126例患者.股骨转子骨折分为稳定或不稳定。指定三名外科医生进行PPM测定。关于人口统计数据,采用卡方检验评估两组间各参数在分类量表上的显著性.采用独立样本t检验或Mann-WhitneyU检验比较两个独立组。计算连续变量的类间相关系数(ICC)值和分类变量的kappa值(κ),以评估观察者之间和观察者之间的一致性。接收器工作特征(ROC)分析用于确定PPM的最佳截止点,以预测不同骨折分类组之间的一致性。一个使用PPM值,其阈值来自普通射线照片图像,和其他使用CT扫描图像。结果在126例股骨转子骨折中,A1(稳定)组包括39例患者(10例男性,29名女性),而A2(不稳定)组由87名患者(14名男性,73名女性)(不显著,NS).观察者间协议的类内相关系数(ICC)值为0.796(0.723-0.852),0.664(0.554-0.751),第一次检查为0.702(0.601-0.781),第二次检查为0.729(0.635-0.801)。观察者内部协议为0.869(0.819-0.906)和0.603(0.480-0.703)。我们检查了阈值为0.4(A1<0.4,A2=0.4或更高)的PPM值的骨折分类组与基于CT的组的一致性。对于第一次检查,平片和CT扫描图像在骨折分类(稳定或不稳定)方面大多存在“中等”一致性,κ(95CI):0.427(0.266-0.588),0.493(0.335-0.651),和0.359(0.176-0.544),对于第二个,0.418(0.251-0.585),和0.451(0.284-0.620),分别。结论我们提出了一个补充工具,即PPM,允许在修订的AO/OTA分类系统下使用平片X线图像将股骨转子骨折分为A1(稳定)和A2(不稳定)。在这项研究中,0.4的PPM阈值表明观察者间和观察者内的一致性中等.值得注意的是,与使用CT扫描图像进行分类相比,使用来自平片X射线图像的PPM进行骨折分类具有令人满意的一致性。此外,PPM方法提供了一个数字分数。
    Introduction The absence of a precise fracture classification system that classifies pertrochanteric fractures into either stable or unstable contributes to a burden on healthcare and has several major implications. We propose an innovative graphical index, which we refer to as posterior protrusion measures (PPM), using plain lateral view radiograph images for the revised AO Foundation (Arbeitsgemeinschaft für Osteosynthesesfragen)/Orthopedic Trauma Association (AO/OTA) classification system. This study aims to: (i) introduce the use of PPM for classifying fractures into stable or unstable under the revised AO/OTA classification system and set the threshold numeric value, (ii) elucidate the reproducibility of inter and intra-observer agreement, and investigate the consistency of fracture classification using PPM versus computed tomography (CT) scan images. Materials and methods Out of 146 patients identified from the database, a total of 126 patients were enrolled in the study. Pertrochanteric fractures were classified as either stable or unstable. Three surgeons were assigned for PPM determination. Regarding the demographical data, the chi-square test was used to assess the significance of each parameter on a categorical scale between the two groups. The independent sample t-test or the Mann-Whitney U test was used to compare the two independent groups. Interclass correlation coefficient (ICC) values for continuous variables and kappa values (κ) for categorical variables were calculated to assess inter-observer and intra-observer agreement. Receiver-operating characteristic (ROC) analysis was used to determine optimal cut-off points of PPM to predict consistency between separate fracture classification groups, one using PPM values with a threshold derived from plain radiograph images, and the other using CT scan images. Results Among a total of 126 pertrochanteric fractures, the A1 (stable) group consisted of 39 patients (10 males, 29 females), whereas the A2 (unstable) group consisted of 87 patients (14 males, 73 females) (not significant, NS). Intraclass correlation coefficient (ICC) values of PPM for the inter-observer agreement were 0.796 (0.723-0.852), 0.664 (0.554-0.751), and 0.702 (0.601-0.781) at first examination and 0.729 (0.635-0.801) at the second. The intra-observer agreement was 0.869 (0.819-0.906) and 0.603 (0.480-0.703). We examined for consistency of fracture classification group of PPM values with a threshold of 0.4 (A1<0.4, A2=0.4 or more) and CT-based group. For the first examination, there was mostly \"moderate\" agreement in fracture classification (stable or unstable) between plain radiograph and CT scan images, κ (95%CI): 0.427 (0.266-0.588), 0.493 (0.335-0.651), and 0.359 (0.176-0.544), and for the second, 0.418 (0.251-0.585), and 0.451 (0.284-0.620), respectively. Conclusion We propose a supplementary tool, namely PPM that allows for possible alternative classification of pertrochanteric fractures into A1 (stable) and A2 (unstable) using plain radiograph images under the revised AO/OTA classification system. In this study, a PPM threshold value of 0.4 demonstrated a moderate inter- and intra-observer agreement. It is noteworthy to mention that there was a satisfactory consistency of fracture classification using PPM derived from plain radiograph images when compared to classification using CT scan images. In addition, the PPM method provides a numerical score.
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