A Novel Fragment Specific Classification of Complex Olecranon Fractures: 3D Model Design, Radiological Validation and Proposed Surgical Algorithm.

BACKGROUND: Current classifications for proximal ulna fracture patterns rely on qualitative data and cannot inform surgical planning. We propose a new classification system based on a biological and anatomical stress analysis. Our hypothesis is that fragment types in complex fractures can be predicted by the tendon and ligament attachments on the proximal ulna.

METHOD: First, we completed a literature review to identify quantitative data on proximal ulna soft tissue attachments. On this basis, we created a 3D model of ulnar anatomy with SliceOMatic and Catia V5R20 software, and determined likely locations for fragments and fracture lines. The second part of the study was a retrospective radiological study. A level-one trauma radiological database was used to identify CT scans of multifragmentary olecranon fractures from 2009 to 2021. These were reviewed and classified according to the "fragment specific" classification and compared to the Mayo and the Schatzker classifications.

RESULTS: Twelve articles (134 elbows) met the inclusion criteria and seven potential fracture fragments were identified. The radiological study included 67 preoperative CT scans (mean 55 years). The fragments identified were: Posterior (40%), intermediate (42%), tricipital (100%), supinator crest (25%), coronoid (18%), sublime tubercle (12%) and anteromedial facet (18%). Eighteen cases (27%) were classified as Schatzker D (comminutive) and 21 (31%) Mayo 2B (stable comminutive). Inter-rater correlation coefficient (ICC) was 0.71 among 3 observers.

CONCLUSION: This proposed classification system is anatomically based and considers the deforming forces from ligaments and tendons. Having a more comprehensive understanding of complex proximal ulna fractures would lead to more accurate fracture evaluation and surgical planning.