A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS).Aims
Methods
Effective analgesia after total knee arthroplasty (TKA) improves
patient satisfaction, mobility and expedites discharge. This study
assessed whether continuous femoral nerve infusion (CFNI) was superior
to a single-shot femoral nerve block in primary TKA surgery completed
under subarachnoid blockade including morphine. We performed an adequately powered, prospective, randomised,
placebo-controlled trial comparing CFNI of 0.125% bupivacaine Objectives
Methods
Wear debris released from bearing surfaces has been shown to
provoke negative immune responses in the recipient. Excessive wear
has been linked to early failure of prostheses. Analysis using coordinate
measuring machines (CMMs) can provide estimates of total volumetric
material loss of explanted prostheses and can help to understand
device failure. The accuracy of volumetric testing has been debated,
with some investigators stating that only protocols involving hundreds
of thousands of measurement points are sufficient. We looked to
examine this assumption and to apply the findings to the clinical
arena. We examined the effects on the calculated material loss from
a ceramic femoral head when different CMM scanning parameters were
used. Calculated wear volumes were compared with gold standard gravimetric
tests in a blinded study. Objectives
Methods
