The success rates of two-stage revision arthroplasty for infection have evolved since their early description. The implementation of internationally accepted outcome criteria led to the readjustment of such rates. However, patients who do not undergo reimplantation are usually set aside from these calculations. The aim of this study was to investigate the outcomes of two-stage revision arthroplasty when considering those who do not undergo reimplantation, and to investigate the characteristics of this subgroup. A retrospective cohort study was conducted. Patients with chronic hip or knee periprosthetic joint infection (PJI) treated with two-stage revision between January 2010 and October 2018, with a minimum follow-up of one year, were included. Variables including demography, morbidity, microbiology, and outcome were collected. The primary endpoint was the eradication of infection. Patients who did not undergo reimplantation were analyzed in order to characterize this subgroup better.Aims
Methods
Currently, the US Center for Medicaid and Medicare Services (CMS) has been testing bundled payments for revision total joint arthroplasty (TJA) through the Bundled Payment for Care Improvement (BPCI) programme. Under the BPCI, bundled payments for revision TJAs are defined on the basis of diagnosis-related groups (DRGs). However, these DRG-based bundled payment models may not be adequate to account appropriately for the varying case-complexity seen in revision TJAs. The 2008-2014 Medicare 5% Standard Analytical Files (SAF5) were used to identify patients undergoing revision TJA under DRG codes 466, 467, or 468. Generalized linear regression models were built to assess the independent marginal cost-impact of patient, procedural, and geographic characteristics on 90-day costs.Aims
Methods
The aim of this study was to conduct the largest low contact stress (LCS) retrieval study to elucidate the failure mechanisms of the Porocoat and Duofix femoral component. The latter design was voluntarily recalled by the manufacturer. Uncemented LCS explants were divided into three groups: Duofix, Porocoat, and mixed. Demographics, polyethylene wear, tissue ingrowth, and metallurgical analyses were performed.Aims
Materials and Methods
Increasing innovation in rapid prototyping (RP)
and additive manufacturing (AM), also known as 3D printing, is bringing
about major changes in translational surgical research. This review describes the current position in the use of additive
manufacturing in orthopaedic surgery. Cite this article:
The aim of this study was to present data on 11 459 patients
who underwent total hip (THA), total knee (TKA) or unicompartmental
knee arthroplasty (UKA) between November 2002 and April 2014 with
aspirin as the primary agent for pharmacological thromboprophylaxis. We analysed the incidence of deep vein thrombosis (DVT) and pulmonary
embolism (PE) then compared the 90-day all-cause mortality with
the corresponding data in the National Joint Registry for England
and Wales (NJR). Aims
Patients and Methods
Satisfaction with care is important to both patients
and to those who pay for it. The Net Promoter Score (NPS), widely
used in the service industries, has been introduced into the NHS
as the ‘friends and family test’; an overarching measure of patient
satisfaction. It assesses the likelihood of the patient recommending
the healthcare received to another, and is seen as a discriminator
of healthcare performance. We prospectively assessed 6186 individuals
undergoing primary lower limb joint replacement at a single university
hospital to determine the Net Promoter Score for joint replacements
and to evaluate which factors contributed to the response. Achieving pain relief (odds ratio (OR) 2.13, confidence interval
(CI) 1.83 to 2.49), the meeting of pre-operative expectation (OR
2.57, CI 2.24 to 2.97), and the hospital experience (OR 2.33, CI
2.03 to 2.68) are the domains that explain whether a patient would
recommend joint replacement services. These three factors, combined
with the type of surgery undertaken (OR 2.31, CI 1.68 to 3.17),
drove a predictive model that was able to explain 95% of the variation
in the patient’s recommendation response. Though intuitively similar,
this ‘recommendation’ metric was found to be materially different
to satisfaction responses. The difference between THR (NPS 71) and
TKR (NPS 49) suggests that no overarching score for a department
should be used without an adjustment for case mix. However, the
Net Promoter Score does measure a further important dimension to
our existing metrics: the patient experience of healthcare delivery. Cite this article:
