This study aimed to investigate the estimated change in primary and revision arthroplasty rate in the Netherlands and Denmark for hips, knees, and shoulders during the COVID-19 pandemic in 2020 (COVID-period). Additional points of focus included the comparison of patient characteristics and hospital type (2019 vs COVID-period), and the estimated loss of quality-adjusted life years (QALYs) and impact on waiting lists. All hip, knee, and shoulder arthroplasties (2014 to 2020) from the Dutch Arthroplasty Register, and hip and knee arthroplasties from the Danish Hip and Knee Arthroplasty Registries, were included. The expected number of arthroplasties per month in 2020 was estimated using Poisson regression, taking into account changes in age and sex distribution of the general Dutch/Danish population over time, calculating observed/expected (O/E) ratios. Country-specific proportions of patient characteristics and hospital type were calculated per indication category (osteoarthritis/other elective/acute). Waiting list outcomes including QALYs were estimated by modelling virtual waiting lists including 0%, 5% and 10% extra capacity.Aims
Methods
There is an apparent need for easily accessible research data on Periprosthetic hip joint infections (PJI)(1). Administrative discharge registers could be a valuable single-sources for this purpose, and studies originating from such registers have been published(2–4). However, the quality of routinely collected data for administrative purposes may be questionable for use in epidemiological research. The aim of this study was to estimate the positive predictive value of the International Classification of Disease 10th revision (ICD-10) periprosthetic hip joint infection diagnose code T84.5. The study was performed as a cross-sectional study on data extracted from the Danish National Patient Register. Patients with a registration of performed surgical treatment for hip PJI were identified via the ICD-10 code T84.5 (Infection and inflammatory reaction due to internal joint prosthesis) in association with hip-joint associated surgical procedure codes. Medical records of the identified patients (n=283) were verified for the existence of a periprosthetic hip joint infection. Positive predictive values with 95% confidence intervals (95% CI) were calculated. A T84.5 diagnosis code irrespective of the associated surgical procedure code had a positive predictive value of 85 % (95% CI: 80–89). Stratified to T84.5 in combination with an infection-specific surgical procedure code the positive predictive value increased to 86% (95% CI: 80–91), and in combination with a noninfection-specific surgical procedure code decreased to 82% (95% CI: 72–89). This study is the first to evaluate the only discharge diagnose code of prosthesis-related infection in an administrative discharge register. It is apparent, that codes in administrative discharge registers are prone to misclassification on an administrative level, either by wrongful coding by the physician or administrative personal in the registration process. Misclassification must be expected and taken into consideration when using single-source administrative discharge registers for epidemiological research on periprosthetic hip joint infection. We believe that the periprosthetic hip joint infection diagnose code can be of use in single-source register based studies, but preferably should be used in combination with alternate data sources to ensure higher validity(5) This study is funded in part by the Lundbeck foundation Centre for Fast-track Hip and Knee Surgery, Denmark.
The Danish Hip Arthroplasty Register (DHR) is a national database on total hip arthroplasties (THAs) with a high completeness and validity of registration for primary procedures. The aim was to validate the registration in DHR for revisions due to Prosthetic Joint Infection (PJI). We identified a cohort of patients in the DHR who underwent primary THA from January 1, 2005 to December 31, 2012 and we followed these patients until first-time revision, death, emigration or December 31, 2012. The PJI diagnosis registered was tested against a gold standard encompassing information from microbiology, prescription, and clinical biochemistry registries in combination with clinical findings retrieved from medical records. We estimated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) with 95% confidence interval (CI) for PJI in DHR alone and in DHR combined with microbiology registries. Out of 37,828 primary THAs, 1,382 were registered with any revision, 232 of which were due to PJI. For PJI revisions in DHR, the sensitivity was 67.0% (CI: 61.0 – 72.6), specificity 95.2% (CI: 93.8 – 96.4), PPV 77.2% (CI: 71.2 – 82.4), and NPV 92.3% (CI 90.7 – 93.8). Combining DHR with microbiology registries led to a notable increased in the sensitivity for PJI revision to 90.3% (CI: 86.1 – 93.5) and likewise for specificity 99.6% (CI: 99.1 – 99.9), PPV 98.4% (CI: 95.9 – 99.6) and NPV 98.5% (CI: 97.6 – 99.1). Only two thirds of PJI revisions were captured in DHR and the PPV was moderate. However, combining DHR with microbiology registries improved the accuracy remarkably. The study was supported by Region of Southern Denmark and Lillebaelt Hospitals.
9,596 of the 280,201 primary THRs, had been revised. Ten-years survival was 91.9% (95% CI: 91.5 – 92.3) in Denmark, 93.9% (95% CI: 93.6–94.1) in Sweden, and 92.6% (95% CI: 92.3–93.0) in Norway. In Sweden and Norway 23% of revisions were due to dislocation, compared to 34% in Denmark. Replacement of only cup or liner constituted 29% of the revisions in Sweden, 33% in Norway, and 44% in Denmark.
We compared patients’ characteristics and outcome following THA in private and public hos-pitals.
To detect eventual difference in patient characteristics- age, gender, diagnosis leading to THA, Carlson’s comorbidity score and Charnley category were evaluated. We matched 3 658 cases operated in private with 3 658 controllers operated in public hospitals on propensity score. Scoring parameters were age, gender, diagnosis leading to THA, Carlson’s comorbidity score, Charnley category, operating time, type of anesthesia and type of prosthesis. We used multivariate logistic regression on propensity score matched data to assess association between type of hospital and outcome by computing relative risks and 95% Confidence Interval (CI). Outcomes were perioperative complications, readmission within 3 months, re-operation within 2 years, implant failure after 5 years, and mortality within 3 months of surgery.
Patients in private and propensity matched controls from public hospitals showed no differences in age, gender, diagnosis leading to THA, Carlson’s comorbidity score, Charnley category, operating time, type of anesthesia and type of prosthesis (p-value <
0,0001). Based on matched data, private hospitals had lower relative risk for perioperative complications (0.39, 0.26–0.60), reoperations (0.59, 0.41–0.83) and readmissions (0.57, 0.42–0.77) compared with public. There was no difference in mortality or implant failure.
We found significant difference between patient characteristics operated at public versus private hospitals. No difference was evident regarding mortality and implant failure but for complications, reoperations and readmissions between private and public hospitals.
Further, we will present data on 90 days cause of death following primary THR and predictors for death, including age, gender and comorbidity (analyses are not finished yet).