AO Clinical Investigation and Documentation, Dübendorf, Switzerland (now Upper Extremities, Schulthess Klinik, Zürich, Switzerland).
Carolinas Medical Center, Department of Orthopaedic Surgery, Charlotte, NC, USA.
J Shoulder Elbow Surg. 2014 Feb;23(2):189-96. doi: 10.1016/j.jse.2013.07.040. Epub 2013 Sep 27.
A comprehensive system has been developed by the AO Classification Advisory Group to allow in-depth classification of scapular fractures for clinical research and surgical decision making. This paper evaluates a detailed classification system of scapular body fractures to better address the need for clinical relevance.
Seven experienced shoulder and orthopaedic trauma specialist surgeons participated in a follow-up series of agreement studies to specify and to evaluate the involvement of the body in scapula fractures. The last evaluation was conducted on a consecutive collection of 120 scapula fractures.
There was agreement in 82% of the 120 cases with an overall κ of 0.75 when the surgeons identified body (B) fractures. Surgeons were in full agreement about involvement of the lateral inferior, medial, and superior borders in 72%, 51%, and 69% of the 101 cases identified with body involvement, respectively. The proportion of correctly classified cases with lateral inferior, medial, and superior border involvements was 78% or greater.
Body involvement can be reliably identified by use of 3-dimensional computed tomography images. Surgeons could reliably and accurately identify superior, medial, and lateral border involvement, which is considered clinically relevant and likely sufficient for the treatment decision process and outcome prognosis. It should be applied by surgeons with a special interest in the shoulder in the framework of clinical routine as well as in research activities.
AO 分类咨询小组开发了一个综合系统，可对肩胛骨折进行深入分类，以便于临床研究和手术决策。本文评估了一种详细的肩胛体骨折分类系统，以更好地满足临床相关性的需求。
7 名经验丰富的肩部和骨科创伤专家参与了后续的一致性研究系列，以明确和评估肩胛体骨折的受累情况。最后一次评估是对连续收集的 120 例肩胛骨折进行的。
在 120 例病例中，有 82%的病例达成一致，当外科医生识别肩胛体（B）骨折时，总体 κ 值为 0.75。在有肩胛体受累的 101 例病例中，外科医生对侧下方、内侧和上方边界受累的一致性分别为 72%、51%和 69%。外侧下方、内侧和上方边界受累的正确分类比例均为 78%或更高。
使用三维 CT 图像可以可靠地识别肩胛体受累。外科医生可以可靠、准确地识别上、内侧和外侧边界受累，这被认为与临床相关，可能足以用于治疗决策过程和预后预测。它应该由对肩部特别感兴趣的外科医生在临床常规和研究活动中应用。
