The influence of metabolic syndrome (MetS) on the outcome after hip and knee arthroplasty is debated. We aimed to investigate the change in patient-reported outcome measure (PROM) scores after hip and knee arthroplasty, comparing patients with and without MetS. From 1 May 2017 to 30 November 2019, a prospective cohort of 2,586 patients undergoing elective unilateral hip and knee arthroplasty was established in Denmark. Data from national registries and a local database were used to determine the presence of MetS. Patients’ scores on Oxford Hip Score (OHS) or Oxford Knee Score (OKS), EuroQol five-dimension five-level questionnaire (EQ-5D-5L), University of California, Los Angeles (UCLA) Activity Scale, and Forgotten Joint Score (FJS) at baseline, three, 12, and 24 months after surgery were collected. Primary outcome was the difference between groups from baseline to 12 months in OHS and OKS. Secondary outcomes were scores of OHS and OKS at three and 24 months and EQ-5D-5L, UCLA Activity Scale, and FJS at three, 12, and 24 months after surgery. Generalized linear mixed model was applied, adjusting for age, sex, Charlson Comorbidity Index, and smoking to present marginal mean and associated 95% CIs.Aims
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The aim of this study was to examine whether socioeconomic status (SES) is associated with a higher risk of infections following total hip arthroplasty (THA) at 30 and 90 days. We obtained individual-based information on SES markers (cohabitation, education, income, and savings) on 103,901 THA patients from Danish health registries between 1 January 1995 and 31 December 2017. The primary outcome measure was any hospital-treated infection (i.e. all infections). The secondary outcomes were further specified to specific hospital-treated infections (pneumonia, urinary tract infection, and periprosthetic joint infection). The primary timepoint was within 90 days. In addition, the outcomes were further evaluated within 30 days. We calculated the cumulative incidence, and used the pseudo-observation method and generalized linear regression to estimate adjusted risk ratios (RRs) with 95% confidence intervals (CIs) for each marker.Aims
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