Retrospective clinical and X-ray-based outcome analysis of a short-stem hip arthroplasty taking into account the operative learning curve over 7 years in the 3-year control course

Abstract

Introduction: Self-monitoring is crucial to work progressively with a high-quality standard. A retrospective analysis is a valuable tool for studying the postoperative outcome of a prosthesis and for evaluating the learning process for the surgeon. Materials and methods: The learning process of one surgeon was analysed in 133 cases of hip arthroplasty. These were divided into seven groups representing the surgical years 2008–2014. Over the course of 3 postoperative years, a total of 655 radiographs were analysed at regarding three radiological quality parameters (centrum-collum-diaphyseal angle (CCD angle), intramedullary fit&fill ratio (FFR), and migration) and ancillary outcome parameters (Harris Hip Score (HHS), blood loss, operating time, and complications). This period was divided into five times: 1st-day post-op, 6 M, 12 M, 24 M, and 36 M. Bivariate Spearman's correlation analysis and pairwise comparisons were performed. Results: The total collective achieved a proximal FFR of over 0.8. The distal prosthesis tip migrated and was located on the lateral cortex within the first months. The CCD angle initially showed a variation with a subsequent constant course. The HHS showed a significant increase (p < 0.001) to over 90 points postoperatively. Over time, the operating time and blood loss decreased. Intraoperative complications existed only at the beginning of the learning phase. A learning curve effect can be determined for almost all parameters by comparing the subject groups. Conclusions: Operative expertise was shown to gain through a learning curve, whereby postoperative results corresponded to the system philosophy of the short hip stem prosthesis. The distal FFR and the distal lateral distance could represent the principle of the prosthesis, which overall could be an interesting approach for verification of a new parameter.