Aims. Older adults with hip fractures are at high risk of experiencing complications after surgery, but estimates of the rate of specific complications vary by study design and follow-up period. The aim of this systematic review was to determine the prevalence of complications in older adults after hip fracture surgery. Methods. MEDLINE, Embase, CINAHL, and CENTRAL databases were searched from inception until 30 June 2023. Studies were included if they reported prevalence data of complications in an unselected, consecutive population of older adults (aged ≥ 60 years) undergoing hip fracture surgery. Results. A total of 95 studies representing 2,521,300 patients were included. For surgery-specific complications, the 30-day prevalence of reoperation was 2.31%, surgical site infection 1.69%, and deep surgical site infection 0.98%; the 365-day prevalence of prosthesis dislocation was 1.11%, fixation failure 1.77%, and periprosthetic or peri-implant fracture 2.23%. For general complications, the 30-day prevalence of acute kidney injury was 1.21%, blood transfusion 25.55%, cerebrovascular accident 0.79%, lower respiratory tract infection 4.08%, myocardial infarction 1.98%, urinary tract infection 7.01%, and venous thromboembolism 2.15%. Conclusion. Complications are prevalent in older adults who have had surgery for a hip fracture. Studies reporting complications after hip fracture surgery varied widely in terms of quality, and we advocate for the routine monitoring of complications in registries and clinical trials to improve the quality of evidence. Cite this article: Bone Joint J 2025;107-B(2):139–148

Aims

Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool.