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Bone & Joint Open
Vol. 6, Issue 1 | Pages 74 - 81
13 Jan 2025
van Veghel MHW van Steenbergen LN Gademan MGJ van den Hout WB Schreurs BW Hannink G

Aims

We estimated the prevalence of people living with at least one hip, knee, or shoulder arthroplasty in the Netherlands.

Methods

We included the first hip (n = 416,333), knee (n = 314,569), or shoulder (n = 23,751) arthroplasty of each patient aged ≥ 40 years between 2007 and 2022 (hip/knee) or 2014 and 2022 (shoulder) from the Dutch Arthroplasty Register (LROI). Data on the size of the Dutch population were obtained from Statistics Netherlands. Annual incidences and deaths from hip and knee arthroplasty since 2010, and shoulder arthroplasty since 2015, were observed from the LROI. Annual incidences and deaths before those years were estimated using Poisson regression analyses and parametric survival models based on a Gompertz distribution. Non-parametric percentile bootstrapping with resampling was used to estimate 95% CIs.


Bone & Joint Open
Vol. 3, Issue 12 | Pages 977 - 990
23 Dec 2022
Latijnhouwers D Pedersen A Kristiansen E Cannegieter S Schreurs BW van den Hout W Nelissen R Gademan M

Aims

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.

Methods

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.