Risk equations for prosthetic joint infections (PJIs) in UK: a retrospective study using the Clinical Practice Research Datalink (CPRD) AURUM and GOLD databases

Perni, Stefano and Prokopovich, Polina ORCID: https://orcid.org/0000-0002-5700-9570 2024. Risk equations for prosthetic joint infections (PJIs) in UK: a retrospective study using the Clinical Practice Research Datalink (CPRD) AURUM and GOLD databases. BMJ Open 14 (5) , e082501. 10.1136/bmjopen-2023-082501

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Abstract

Background: Prosthetic joint infections (PJIs) are a serious negative outcome of arthroplasty with incidence of about 1%. Risk of PJI could depend on local treatment policies and guidelines; no UK-specific risk scoring is currently available. Objective: To determine a risk quantification model for the development of PJI using electronic health records. Design: Records in Clinical Practice Research Datalink (CPRD) GOLD and AURUM of patients undergoing hip or knee arthroplasty between January 2007 and December 2014, with linkage to Hospital Episode Statistics and Office of National Statistics, were obtained. Cohorts’ characteristics and risk equations through parametric models were developed and compared between the two databases. Pooled cohort risk equations were determined for the UK population and simplified through stepwise selection. Results: After applying the inclusion/exclusion criteria, 174 905 joints (1021 developed PJI) were identified in CPRD AURUM and 48 419 joints (228 developed PJI) in CPRD GOLD. Patients undergoing hip or knee arthroplasty in both databases exhibited different sociodemographic characteristics and medical/drug history. However, the quantification of the impact of such covariates (coefficients of parametric models fitted to the survival curves) on the risk of PJI between the two cohorts was not statistically significant. The log-normal model fitted to the pooled cohorts after stepwise selection had a C-statistic >0.7. Conclusions: The risk prediction tool developed here could help prevent PJI through identifying modifiable risk factors pre-surgery and identifying the patients most likely to benefit from close monitoring/preventive actions. As derived from the UK population, such tool will help the National Health Service reduce the impact of PJI on its resources and patient lives.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Pharmacy
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Start Date: 2024-05-07, Type: open-access
Publisher:	BMJ Publishing Group
Funders:	Wellcome Trust
Date of First Compliant Deposit:	16 May 2024
Date of Acceptance:	26 April 2024
Last Modified:	05 Aug 2024 14:44
URI:	https://orca.cardiff.ac.uk/id/eprint/168962

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