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Periprosthetic joint infection (PJI) is one of the most challenging complications following total joint arthroplasty, with a profound impact on patients and healthcare systems worldwide. Affecting up to 2% of knee replacements and 1% of hip replacements, PJIs are responsible for approximately 19% of revision surgeries, representing a staggering financial burden [1,2].
Beyond the economic costs, the human impact is severe. The path from diagnosis to treatment is often laden with uncertainty, and patients face the potential for long-term disability, social isolation, and significant emotional challenges [3,4]. Treatment involves multiple surgeries, prolonged hospitalisations, and extended antibiotic therapy, which can lead to lost income and reduced productivity [1,5]. With long-term mortality rates reaching 26% within five years, the stakes are incredibly high [1].
As the global population ages, the incidence of PJI is expected to rise, placing ever-increasing pressure on healthcare resources [6]. Policymakers have a critical role in mitigating this public health challenge by promoting investment in preventive measures, accelerating research into rapid diagnostics, and ensuring equitable access to solutions [6,7].

Beyond Culture: closing the diagnostic gap in periprosthetic joint infection

The miracle and the menace of modern surgery
The microbiological spectrum associated with PJI further complicates clinical management
Although prevention is paramount, reliable microbiological diagnosis is a key element in managing PJIs [5]. Proper identification of the causative microorganisms and their antibiotic susceptibility profiles is essential for a definitive diagnosis and for determining the most effective antibiotic regimen [5,8].
The Limits of Conventional Diagnosis
Culture-based methods remain the gold standard for this purpose, but they are challenging, time-consuming, and have significant limitations [9,10]. The presence of slow-growing bacteria, polymicrobial infections, and antibiotic-suppressed pathogens often leads to inconsistent or false-negative results [7,9,11]. These microbiological gaps highlight the critical need for advanced molecular biology to overcome the limitations of traditional techniques [12-14].
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PJI Case Study: A Diagnostic Dilemma

  • A 72-year-old retired patient, who had undergone a total hip replacement (THR) for severe osteoarthritis one year prior, presented to the orthopaedic team with persistent right hip pain and a chronically draining sinus tract over the greater trochanter, making ambulation difficult and significantly impacting his quality of life.

  • Initial bloodwork was highly indicative of infection, revealing a C-reactive protein (CRP) of 200 mg/L and a white cell count (WCC) of 20 x 10^9/L. Radiographs confirmed loosening of the femoral component. A critical complicating factor was that the patient had just finished a course of oral antibiotics for an unrelated dental infection.

  • A hip aspiration was performed, yielding a small volume of purulent synovial fluid. Due to the limited sample, only a portion could be sent for microbiological analysis. It was inoculated into aerobic and anaerobic culture bottles; microscopy of the fluid showed numerous white blood cells but, crucially, no visible organisms. After 14 days of extended incubation, the cultures remained sterile, with no bacterial growth detected.

  • Without a definitive pathogen identification to guide therapy, the clinical team was forced to proceed based on high clinical suspicion alone. The patient underwent the first stage of a two-stage revision arthroplasty. This major procedure involved removing the hip implant, extensive debridement of all infected bone and soft tissue, and the insertion of a temporary antibiotic-eluting cement spacer. He was subsequently treated empirically with a prolonged course of broad-spectrum intravenous antibiotics. Following a long and arduous recovery, he required a second major surgery months later to implant a new prosthesis.

  • This case perfectly illustrates how the limitations of culture-based diagnostics; confounded by low sample volume and prior antibiotic use; can lead to a diagnostic dead-end. The lack of an early, precise microbiological diagnosis delayed targeted treatment and subjected the patient to a lengthy, multi-stage surgical process.

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This case perfectly illustrates how current diagnostic barriers can lead to poor outcomes.

A New Paradigm: The DRAIGON Project's WGS-Based Approach

A new molecular approach has the potential to revolutionise the management of PJI. While it still requires an initial positive culture, it aims to significantly accelerate diagnosis by analysing bacterial DNA directly from the positive growth medium (e.g., blood or synovial fluid cultures).

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The EU-funded DRAIGON project is developing such a tool, based on accelerated whole-genome sequencing (WGS) coupled with AI-assisted data analysis [15,16]. In a single assay, this platform will provide pathogen identification, typing, antimicrobial resistance (AMR) profiling, and treatment guidance based on a genomic antibiogram [14]. This breakthrough combination of WGS and AI promises to change the paradigm of PJI management, ensuring that patients receive accurate, targeted treatment plans in a fraction of the time, dramatically improving outcomes and reducing the burden on patients and healthcare systems alike. 

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Together, we can make a difference: 

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Join us in our mission to combat antimicrobial resistance (AMR)
and safeguard the health of future generations.

  1. Patel R. Periprosthetic joint infection. N Engl J Med. 2023;388(3):251-262. https://doi.org/10.1056/NEJMra2203477

  2. Izakovicova P, Borens O, Trampuz A. Periprosthetic joint infection: current concepts and outlook. EFORT Open Rev. 2019;4:482-494. https://doi.org/10.1302/2058-5241.4.180092

  3. Aichmair A, Pastl D, Frank BJ, et al. High demand for psychological support in patients who have periprosthetic hip and knee joint infections: an analysis of 13,976 patients. J Arthroplasty. 2024;39(9):2575-2580. https://doi.org/10.1016/j.arth.2024.07.012

  4. Walter N, Mohokum M, Loew T, Rupp M, Alt V. Healing beyond the joint: addressing mental health in periprosthetic joint infection in a prospective longitudinal study. J Psychosom Res. 2024;177:111559. https://doi.org/10.1016/j.jpsychores.2023.111559

  5. Miller R, Higuera CA, Wu J, Klika A, Babic M, Piuzzi NS. Periprosthetic joint infection: a review of antibiotic treatment. JBJS Rev. 2020;8(7):e2000021. https://doi.org/10.2106/JBJS.RVW.20.00021

  6. Zardi EM, Franceschi F. Prosthetic joint infection. A relevant public health issue. J Infect Public Health. 2020;13(12):1888-1891. https://doi.org/10.1016/j.jiph.2020.09.006

  7. Beam E, Osmon DR. Prosthetic joint infection update. Infect Dis Clin North Am. 2018;32(4):843-859. https://doi.org/10.1016/j.idc.2018.06.006

  8. McNally M, Sousa R, Wouthuyzen-Bakker M, et al. The EBJIS definition of periprosthetic joint infection: a practical guide for clinicians. Bone Joint J. 2021;103-B(1):18-24. https://doi.org/10.1302/0301-620X.103B1.BJJ-2020-1381.R1

  9. Oliva A, Miele MC, Al Ismail D, et al. Challenges in the microbiological diagnosis of implant-associated infections: a summary of the current knowledge. Front Microbiol. 2021;12:750460. https://doi.org/10.3389/fmicb.2021.750460

  10. Tan TL, Kheir MM, Shohat N, et al. Culture-negative periprosthetic joint infection. JBJS Open Access. 2018;3(3):e0060. https://doi.org/10.2106/JBJS.OA.17.00060

  11. Benito N, Mur I, Ribera A, et al. The different microbial etiology of prosthetic joint infections according to route of acquisition and time after prosthesis implantation, including the role of multidrug-resistant organisms. J Clin Med. 2019;8(5):668. https://doi.org/10.3390/jcm8050668

  12. Huang C, Huang Y, Wang Z, et al. Multiplex PCR-based next-generation sequencing as a novel, targeted and accurate molecular approach for periprosthetic joint infection diagnosis. Front Microbiol. 2023;14:1181348. https://doi.org/10.3389/fmicb.2023.1181348

  13. Yin H, Xu D, Wang D. Diagnostic value of next-generation sequencing to detect periprosthetic joint infection. BMC Musculoskelet Disord. 2021;22(1):252. https://doi.org/10.1186/s12891-021-04116-9

  14. Huang Z, Li W, Lee GC, et al. Metagenomic next-generation sequencing of synovial fluid demonstrates high accuracy in prosthetic joint infection diagnostics. Bone Joint Res. 2020;9(7):440-449. https://doi.org/10.1302/2046-3758.97.BJR-2019-0325.R2

  15. Boolchandani M, D’Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet. 2019;20(6):356-370. https://doi.org/10.1038/s41576-019-0108-4

  16. Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet. 2019;20(6):341-355. https://doi.org/10.1038/s41576-019-0113-7

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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them.​

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101137383.

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