Aims

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.

Objectives. The Oxford Hip and Knee Scores (OHS, OKS) have been demonstrated to vary according to age and gender, making it difficult to compare results in cohorts with different demographics. The aim of this paper was to calculate reference values for different patient groups and highlight the concept of normative reference data to contextualise an individual’s outcome. Methods. We accessed prospectively collected OHS and OKS data for patients undergoing lower limb joint arthroplasty at a single orthopaedic teaching hospital during a five-year period. T-scores were calculated based on the OHS and OKS distributions. . Results. Data were obtained from 3203 total hip arthroplasty (THA) patients and 2742 total knee arthroplasty (TKA) patients. The mean age of the patient was 68.0 years (. sd. 11.3, 58.4% women) in the THA group and in 70.2 (. sd. 9.4; 57.5% women) in the TKA group. T-scores were calculated for age and gender subgroups by operation. Different T-score thresholds are seen at different time points pre and post surgery. Values are further stratified by operation (THA/TKA) age and gender. Conclusions. Normative data interpretation requires a fundamental shift in the thinking as to the use of the Oxford Scores. Instead of reporting actual score points, the patient is rated by their relative position within the group of all patients undergoing the same procedure. It is proposed that this form of transformation is beneficial (a) for more appropriately comparing different patient cohorts and (b) informing an individual patient how they are progressing compared with others of their age and gender. Cite this article: Bone Joint Res 2015;4:137–144

Objectives

We wanted to investigate regional variations in the organisms reported to be causing peri-prosthetic infections and to report on prophylaxis regimens currently in use across England.