Division of Surgery Oncology Reproductive Medicine and Anaesthetics, Imperial College London, UK.
J Shoulder Elbow Surg. 2011 Oct;20(7):1125-32. doi: 10.1016/j.jse.2011.01.020. Epub 2011 Apr 9.
This study evaluated several classification systems and expert surgeons' anatomic understanding of these complex injuries based on a consecutive series of patients. We hypothesized that current proximal humeral fracture classification systems, regardless of imaging methods, are not sufficiently reliable to aid clinical management of these injuries.
Complex fractures in 96 consecutive patients were investigated by generation of rapid sequence prototyping models from computed tomography Digital Imaging and Communications in Medicine (DICOM) imaging data. Four independent senior observers were asked to classify each model using 4 classification systems: Neer, AO, Codman-Hertel, and a prototype classification system by Resch. Interobserver and intraobserver κ coefficient values were calculated for the overall classification system and for selected classification items.
The κ coefficient values for the interobserver reliability were 0.33 for Neer, 0.11 for AO, 0.44 for Codman-Hertel, and 0.15 for Resch. Interobserver reliability κ coefficient values were 0.32 for the number of fragments and 0.30 for the anatomic segment involved using the Neer system, 0.30 for the AO type (A, B, C), and 0.53, 0.48, and 0.08 for the Resch impaction/distraction, varus/valgus and flexion/extension subgroups, respectively. Three-part fractures showed low reliability for the Neer and AO systems.
Currently available evidence suggests fracture classifications in use have poor intra- and inter-observer reliability despite the modality of imaging used thus making treating these injuries difficult as weak as affecting scientific research as well. This study was undertaken to evaluate the reliability of several systems using rapid sequence prototype models.
Overall interobserver κ values represented slight to moderate agreement. The most reliable interobserver scores were found with the Codman-Hertel classification, followed by elements of Resch's trial system. The AO system had the lowest values. The higher interobserver reliability values for the Codman-Hertel system showed that is the only comprehensive fracture description studied, whereas the novel classification by Resch showed clear definition in respect to varus/valgus and impaction/distraction angulation.
本研究评估了几种分类系统以及专家对这些复杂损伤的解剖理解，这是基于一系列连续的患者。我们假设，目前的肱骨近端骨折分类系统，无论成像方法如何，都不足以帮助临床管理这些损伤。
使用从 CT 数字成像和通信(DICOM)成像数据生成快速序列原型模型的方法对 96 例连续患者的复杂骨折进行了研究。四名独立的资深观察者被要求使用 4 种分类系统（Neer、AO、Codman-Hertel 和 Resch 原型分类系统）对每个模型进行分类。计算了总体分类系统和选定分类项目的观察者间和观察者内 κ 系数值。
观察者间可靠性的 κ 系数值为 Neer 为 0.33，AO 为 0.11，Codman-Hertel 为 0.44，Resch 为 0.15。Neer 系统中，骨折块数和涉及解剖段的观察者间可靠性 κ 系数值分别为 0.32 和 0.30，AO 型（A、B、C）为 0.30，Resch 冲击/分离、内翻/外翻和屈曲/伸展亚组分别为 0.53、0.48 和 0.08。三部分骨折在 Neer 和 AO 系统中的可靠性较低。
目前的证据表明，尽管使用了成像方式，但现有的骨折分类方法的观察者内和观察者间的可靠性都很差，这使得治疗这些损伤变得困难，就像影响科学研究一样。本研究旨在使用快速序列原型模型评估几种系统的可靠性。
总体观察者间 κ 值表示轻度至中度一致性。发现观察者间评分最可靠的是 Codman-Hertel 分类，其次是 Resch 试用系统的要素。AO 系统的评分最低。Codman-Hertel 系统观察者间可靠性较高，表明该系统是唯一研究的全面骨折描述，而 Resch 的新分类在内外翻和冲击/分离角度方面有明确的定义。
