Prediction of Early Periprosthetic Joint Infection After Total Hip Arthroplasty

Erik Bülow; Ute Hahn; Ina Trolle Andersen; Ola Rolfson; Alma B Pedersen; Nils P Hailer

doi:10.2147/CLEP.S347968

Prediction of Early Periprosthetic Joint Infection After Total Hip Arthroplasty

Clin Epidemiol. 2022 Mar 4:14:239-253. doi: 10.2147/CLEP.S347968. eCollection 2022.

Authors

Erik Bülow^{1

2}, Ute Hahn^{3

4}, Ina Trolle Andersen³, Ola Rolfson^{1

2}, Alma B Pedersen^{3

5}, Nils P Hailer⁶

Affiliations

¹ The Swedish Arthroplasty Register, Centre of Registers Västra Götaland, Gothenburg, Sweden.
² Department of Orthopaedics, Institute of Clinical Sciences, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
³ Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
⁴ Department of Mathematics, Aarhus University, Aarhus, Denmark.
⁵ Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
⁶ Department of Surgical Sciences/Orthopaedics, Uppsala University Hospital, Uppsala, Sweden.

Abstract

Purpose: To develop a parsimonious risk prediction model for periprosthetic joint infection (PJI) within 90 days after total hip arthroplasty (THA).

Patients and methods: We used logistic LASSO regression with bootstrap ranking to develop a risk prediction model for PJI within 90 days based on a Swedish cohort of 88,830 patients with elective THA 2008-2015. The model was externally validated on a Danish cohort with 18,854 patients.

Results: Incidence of PJI was 2.45% in Sweden and 2.17% in Denmark. A model with the underlying diagnosis for THA, body mass index (BMI), American Society for Anesthesiologists (ASA) class, sex, age, and the presence of five defined comorbidities had an area under the curve (AUC) of 0.68 (95% CI: 0.66 to 0.69) in Sweden and 0.66 (95% CI: 0.64 to 0.69) in Denmark. This was superior to traditional models based on ASA class, Charlson, Elixhauser, or the Rx Risk V comorbidity indices. Internal calibration was good for predicted probabilities up to 10%.

Conclusion: A new PJI prediction model based on easily accessible data available before THA was developed and externally validated. The model had superior discriminatory ability compared to ASA class alone or more complex comorbidity indices and had good calibration. We provide a web-based calculator (https://erikbulow.shinyapps.io/thamortpred/) to facilitate shared decision making by patients and surgeons.

Keywords: clinical decision-making tool; external validation; orthopaedics; prediction model; total hip arthroplasty; web calculator.

Grants and funding

This study was in part support by a grant to NPH from the Swedish Research Council (VR 2021-00980).