Introduction Periprosthetic femur fractures (PPFF) are increasing in incidence and management of such injuries requires a specialized skill set combined with detailed knowledge of component design. To assist with planning, computed tomography (CT) can be used pre-operatively to give a surgeon more information. No study to date has shown the utility of obtaining preoperative CT. The goal of this study is to show that CT is a useful diagnostic adjunct and report any differences in how subspecialties such as orthopedic traumatologists and arthroplasty surgeons use it. Methods Seventeen PPFF cases met our inclusion criteria. They were shown to six faculty, three trauma and three arthroplasty surgeons. They viewed the plain radiographs and then CTs. After each they filled out the same questionnaire that included their assessment of diagnosis and proposed treatment plan both before and after access to CT imaging. Fleiss and Cohen kappa were used to compare inter- and intra-observer reliability. Results The interobserver kappa values () in diagnosis were 0.348 pre- and 0.371 post-CT, while trauma and arthroplasty were 0.328 to 0.260 and 0.821 to 0.881 respectively. The interobserver reliability in treatment was 0.336 pre- and 0.254 post-CT, while trauma and arthroplasty were 0.323 to 0.288 and 0.688 to 0.519. For intraobserver the average for diagnosis and treatment were 0.818 and 0.671. Broken down by subspecialty they were 0.874 and 0.831 and 0.762 and 0.510 for trauma and arthroplasty. There were 11 diagnostic and 24 treatment changes. Conclusion CT provides diagnostic changes 10% and treatment changes 24% of the time. However, it does not lead to greater agreement among the surgeons on either. Arthroplasty uses CT more to guide both their treatment and the diagnosis, and they agree more than trauma surgeons. Most of the treatment changes come from adding or removing a plate, and the most common diagnostic change was shared by A to B1 and B2 to B3. This suggests fracture extension and bone stock are better evaluated by CT.
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http://dx.doi.org/10.7759/cureus.38785 | DOI Listing |
J Coll Physicians Surg Pak
January 2025
Department of Orthopaedics, Gansu Provincial Hospital, Lanzhou, China.
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View Article and Find Full Text PDFBackground: The purpose of this study was to assess impingement-free internal rotation (IR) in a virtual reverse shoulder arthroplasty simulation using a Statistical Shape Model based on scapula size.
Methods: A database of over 10,000 scapulae utilized for preoperative planning for shoulder arthroplasty was analyzed with a Statistical Shape Model to obtain 5 scapula sizes including the mean and 2 standard deviations. For each scapula model, one glenosphere size (33-42 mm) was selected as the best fit based on consensus among 3 shoulder surgeons.
Arch Orthop Trauma Surg
January 2025
Bioengineering Laboratory, Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA.
Introduction: Periprosthetic joint infection (PJI) following total hip arthroplasty (THA) remains a devastating complication for patients and surgeons. Given the implications of these infections and the current paucity of risk calculators utilizing machine learning (ML), this study aimed to develop an ML algorithm that could accurately identify risk factors for developing a PJI following primary THA using a national database.
Materials And Methods: A total of 51,053 patients who underwent primary THA between 2013 and 2020 were identified using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.
Arch Orthop Trauma Surg
January 2025
Division of Orthopedic Surgery, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel.
J Orthop Trauma
January 2025
George Washington University School of Medicine and Health Sciences, Department of Orthopaedic Surgery, 2300 M St, Washington, DC, 20037.
Objectives: To identify the rate of fixation failure following femoral neck fracture (FNF) fixation in young adults within a national database.
Methods: Design: Retrospective cohort study.
Setting: National all-payer claims database.
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