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The Bone & Joint Journal
Vol. 104-B, Issue 12 | Pages 1313 - 1322
1 Dec 2022
Yapp LZ Clement ND Moran M Clarke JV Simpson AHRW Scott CEH

Aims

The aim of this study was to assess factors associated with the estimated lifetime risk of revision surgery after primary knee arthroplasty (KA).

Methods

All patients from the Scottish Arthroplasty Project dataset undergoing primary KA during the period 1 January 1998 to 31 December 2019 were included. The cumulative incidence function for revision and death was calculated up to 20 years. Adjusted analyses used cause-specific Cox regression modelling to determine the influence of patient factors. The lifetime risk was calculated as a percentage for patients aged between 45 and 99 years using multiple-decrement life table methodology.


The Bone & Joint Journal
Vol. 104-B, Issue 4 | Pages 452 - 463
1 Apr 2022
Elcock KL Carter TH Yapp LZ MacDonald DJ Howie CR Stoddart A Berg G Clement ND Scott CEH

Aims

Access to total knee arthroplasty (TKA) is sometimes restricted for patients with severe obesity (BMI ≥ 40 kg/m2). This study compares the cost per quality-adjusted life year (QALY) associated with TKA in patients with a BMI above and below 40 kg/m2 to examine whether this is supported.

Methods

This single-centre study compared 169 consecutive patients with severe obesity (BMI ≥ 40 kg/m2) (mean age 65.2 years (40 to 87); mean BMI 44.2 kg/m2 (40 to 66); 129/169 female) undergoing unilateral TKA to a propensity score matched (age, sex, preoperative Oxford Knee Score (OKS)) cohort with a BMI < 40 kg/m2 in a 1:1 ratio. Demographic data, comorbidities, and complications to one year were recorded. Preoperative and one-year patient-reported outcome measures (PROMs) were completed: EuroQol five-dimension three-level questionnaire (EQ-5D-3L), OKS, pain, and satisfaction. Using national life expectancy data with obesity correction and the 2020 NHS National Tariff, QALYs (discounted at 3.5%), and direct medical costs accrued over a patient’s lifetime, were calculated. Probabilistic sensitivity analysis (PSA) was used to model variation in cost/QALY for each cohort across 1,000 simulations.