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Bone & Joint Open
Vol. 5, Issue 1 | Pages 60 - 68
24 Jan 2024
Shawon MSR Jin X Hanly M de Steiger R Harris I Jorm L

Aims

It is unclear whether mortality outcomes differ for patients undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA) surgery who are readmitted to the index hospital where their surgery was performed, or to another hospital.

Methods

We analyzed linked hospital and death records for residents of New South Wales, Australia, aged ≥ 18 years who had an emergency readmission within 90 days following THA or TKA surgery between 2003 and 2022. Multivariable modelling was used to identify factors associated with non-index readmission and to evaluate associations of readmission destination (non-index vs index) with 90-day and one-year mortality.


The Bone & Joint Journal
Vol. 103-B, Issue 6 | Pages 1119 - 1126
1 Jun 2021
Ivy MI Sharma K Greenwood-Quaintance KE Tande AJ Osmon DR Berbari EF Mandrekar J Beauchamp CP Hanssen AD Abdel MP Lewallen DG Perry K Block DR Snyder MR Patel R

Aims

The aim of this study was to determine the diagnostic accuracy of α defensin (AD) lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) tests for periprosthetic joint infection (PJI) in comparison to conventional synovial white blood cell (WBC) count and polymorphonuclear neutrophil percentage (PMN%) analysis.

Methods

Patients undergoing joint aspiration for evaluation of pain after total knee arthroplasty (TKA) or total hip arthroplasty (THA) were considered for inclusion. Synovial fluids from 99 patients (25 THA and 74 TKA) were analyzed by WBC count and PMN% analysis, AD LFA, and AD ELISA. WBC and PMN% cutoffs of ≥ 1,700 cells/mm3 and ≥ 65% for TKA and ≥ 3,000 cells/mm3 and ≥ 80% for THA were used, respectively. A panel of three physicians, all with expertise in orthopaedic infections and who were blinded to the results of AD tests, independently reviewed patient data to diagnose subjects as with or without PJI. Consensus PJI classification was used as the reference standard to evaluate test performances. Results were compared using McNemar’s test and area under the receiver operating characteristic curve (AUC) analysis.


The Bone & Joint Journal
Vol. 102-B, Issue 12 | Pages 1682 - 1688
1 Dec 2020
Corona PS Vicente M Carrera L Rodríguez-Pardo D Corró S

Aims

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.

Methods

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.


The Bone & Joint Journal
Vol. 102-B, Issue 7 | Pages 959 - 964
1 Jul 2020
Malik AT Li M Khan SN Alexander JH Li D Scharschmidt TJ

Aims

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.

Methods

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.


The Bone & Joint Journal
Vol. 101-B, Issue 8 | Pages 941 - 950
1 Aug 2019
Scott CEH MacDonald DJ Howie CR

Aims

The EuroQol five-dimension (EQ-5D) questionnaire is a widely used multiattribute general health questionnaire where an EQ-5D < 0 defines a state ‘worse than death’ (WTD). The aim of this study was to determine the proportion of patients awaiting total hip arthroplasty (THA) or total knee arthroplasty (TKA) in a health state WTD and to identify associations with this state. Secondary aims were to examine the effect of WTD status on one-year outcomes.

Patients and Methods

A cross-sectional analysis of 2073 patients undergoing 2073 THAs (mean age 67.4 years (sd 11.6; 14 to 95); mean body mass index (BMI) 28.5 kg/m2 (sd 5.7; 15 to 72); 1253 female (60%)) and 2168 patients undergoing 2168 TKAs (mean age 69.3 years (sd 9.6; 22 to 91); BMI 30.8 kg/m2 (sd 5.8; 13 to 57); 1244 female (57%)) were recorded. Univariate analysis was used to identify variables associated with an EQ-5D score < 0: age, BMI, sex, deprivation quintile, comorbidities, and joint-specific function measured using the Oxford Hip Score (OHS) or Oxford Knee Score (OKS). Multivariate logistic regression was performed. EQ-5D and OHS/OKS were repeated one year following surgery in 1555 THAs and 1700 TKAs.


The Bone & Joint Journal
Vol. 100-B, Issue 9 | Pages 1168 - 1174
1 Sep 2018
Zhang L Lix LM Ayilara O Sawatzky R Bohm ER

Aims

The aim of this study was to assess the effect of multimorbidity on improvements in health-related quality of life (HRQoL) following total hip arthroplasty (THA) and total knee arthroplasty (TKA).

Patients and Methods

Using data from a regional joint registry for 14 573 patients, HRQoL was measured prior and one year following surgery using the Oxford Hip Score (OHS) and Oxford Knee Score (OKS), and the 12-Item Short-Form Health Survey Physical and Mental Component Summary scores (PCS and MCS, respectively). Multimorbidity was defined as the concurrence of two or more self-reported chronic conditions. A linear mixed-effects model was used to test the effects of multimorbidity and the number of chronic conditions on improvements in HRQoL.


The Bone & Joint Journal
Vol. 97-B, Issue 11 | Pages 1512 - 1518
1 Nov 2015
Courtney PM Melnic CM Gutsche J Hume EL Lee G

Older patients with multiple medical co-morbidities are increasingly being offered and undergoing total joint arthroplasty (TJA). These patients are more likely to require intensive care support, following surgery. We prospectively evaluated the need for intensive care admission and intervention in a consecutive series of 738 patients undergoing elective hip and knee arthroplasty procedures. The mean age was 60.6 years (18 to 91; 440 women, 298 men. Risk factors, correlating with the need for critical care intervention, according to published guidelines, were analysed to identify high-risk patients who would benefit from post-operative critical care monitoring. A total of 50 patients (6.7%) in our series required critical care level interventions during their hospital stay. Six independent multivariate clinical predictors were identified (p < 0.001) including a history of congestive heart failure (odds ratio (OR) 24.26, 95% confidence interval (CI) 9.51 to 61.91), estimated blood loss >  1000 mL (OR 17.36, 95% CI 5.36 to 56.19), chronic obstructive pulmonary disease (13.90, 95% CI 4.78 to 40.36), intra-operative use of vasopressors (OR 8.10, 95% CI 3.23 to 20.27), revision hip arthroplasty (OR 2.71, 95% CI 1.04 to 7.04) and body mass index > 35 kg/m2 (OR 2.70, 95% CI 123 to 5.94). The model was then validated against an independent, previously published data set of 1594 consecutive patients. The use of this risk stratification model can be helpful in predicting which high-risk patients would benefit from a higher level of monitoring and care after elective TJA and aid hospitals in allocating precious critical care resources.

Cite this article: Bone Joint J 2015;97-B:1512–18.