Epidemiology and characteristics of femoral periprosthetic fractures

Abstract

AimsThe aim of this study was to describe the demographic details of patients who sustain a femoral periprosthetic fracture (PPF), the epidemiology of PPFs, PPF characteristics, and the predictors of PPF types in the UK population.MethodsThis is a multicentre retrospective cohort study including adult patients presenting to hospital with a new PPF between 1 January 2018 and 31 December 2018. Data collected included: patient characteristics, comorbidities, anticoagulant use, social circumstances, level of mobility, fracture characteristics, Unified Classification System (UCS) type, and details of the original implant. Descriptive analysis by fracture location was performed, and predictors of PPF type were assessed using mixed-effects logistic regression models.ResultsIn total, 720 femoral PPFs from 27 NHS sites were included. PPF patients were typically elderly (mean 79.9 years (SD 10.6)), female (n = 455; 63.2%), had at least one comorbidity (n = 670; 93.1%), and were reliant on walking aids or bed-/chair-bound prior to admission (n = 419; 61.7%). The study population included 539 (74.9%) hip PPFs, 151 (21.0%) knee PPFs, and 30 (4.2%) dividing type PPFs. For hip (n = 407; 75.5%) and knee (n = 88; 58.3%) arthroplasty UCS B type fractures were most common. Overall, 556 (86.2%) were treated in the presenting hospital and 89 (13.8%) required transfer for treatment. Female sex was the only significant predictor of fracture type (A/B1/C type versus B2/B3) for femoral hip PPFs (odds ratio 0.61 (95% confidence interval 0.41 to 0.91); p = 0.014). Sex, residence type, primary versus revision implant PPF, implant fixation, and time between arthroplasty and PPF were not found to predict fracture type for hip PPFs.ConclusionThis multicentre analysis describes patient and injury factors for patients presenting with femoral PPFs to centres across the UK. These patients are generally elderly and frail, comparable to those sustaining a hip fracture. These data can be useful in planning future services and clinical trials. Cite this article: Bone Joint J 2022;104-B(8):987–996 .