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Bone & Joint Open
Vol. 5, Issue 10 | Pages 937 - 943
22 Oct 2024
Gregor RH Hooper GJ Frampton C

Aims

The aim of this study was to determine whether obesity had a detrimental effect on the long-term performance and survival of medial unicompartmental knee arthroplasties (UKAs).

Methods

This study reviewed prospectively collected functional outcome scores and revision rates of all medial UKA patients with recorded BMI performed in Christchurch, New Zealand, from January 2011 to September 2021. Patient-reported outcome measures (PROMs) were the primary outcome of this study, with all-cause revision rate analyzed as a secondary outcome. PROMs were taken preoperatively, at six months, one year, five years, and ten years postoperatively. There were 873 patients who had functional scores recorded at five years and 164 patients had scores recorded at ten years. Further sub-group analysis was performed based on the patient’s BMI. Revision data were available through the New Zealand Joint Registry for 2,323 UKAs performed during this time period.


Bone & Joint Open
Vol. 4, Issue 10 | Pages 808 - 816
24 Oct 2023
Scott CEH Snowden GT Cawley W Bell KR MacDonald DJ Macpherson GJ Yapp LZ Clement ND

Aims

This prospective study reports longitudinal, within-patient, patient-reported outcome measures (PROMs) over a 15-year period following cemented single radius total knee arthroplasty (TKA). Secondary aims included reporting PROMs trajectory, 15-year implant survival, and patient attrition from follow-up.

Methods

From 2006 to 2007, 462 consecutive cemented cruciate-retaining Triathlon TKAs were implanted in 426 patients (mean age 69 years (21 to 89); 290 (62.7%) female). PROMs (12-item Short Form Survey (SF-12), Oxford Knee Score (OKS), and satisfaction) were assessed preoperatively and at one, five, ten, and 15 years. Kaplan-Meier survival and univariate analysis were performed.


Bone & Joint Open
Vol. 4, Issue 6 | Pages 399 - 407
1 Jun 2023
Yeramosu T Ahmad W Satpathy J Farrar JM Golladay GJ Patel NK

Aims

To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA.

Methods

Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.


Bone & Joint Open
Vol. 3, Issue 7 | Pages 573 - 581
1 Jul 2022
Clement ND Afzal I Peacock CJH MacDonald D Macpherson GJ Patton JT Asopa V Sochart DH Kader DF

Aims

The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA).

Methods

A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.