Post-arthroplasty prosthetic joint infection (PJI) is a significant and common complication [1], frequently necessitating revision surgery [2]. Still, detecting the causative agents of PJI remains a challenge [3]. Accurately identifying pathogenic organisms is crucial for the appropriate treatment and successful recovery from PJI, as it guides the selection of effective antibiotics and surgical strategies, such as primary or secondary revision surgery [1,2].

Pathogenic microorganism culture is currently the prevailing method used to detect causative pathogens in clinical practice [4,5]. Despite advancements in specimen processing and culture techniques, the detection rate of pathogenic microorganisms remains suboptimal [6]. Moreover, the culture process is time-consuming, often spanning several days, delaying effective PJI treatment. Although pathogenic microbial culture remains widely used for detecting pathogenic microbes in PJI, its limitations hinder its clinical utility. Firstly, it exhibits low sensitivity. A meta-analysis by Rodriguez-Merchan [7] reported a sensitivity of only 67.6 % for preoperative joint fluid aspiration culture, with some studies demonstrating even lower sensitivity rates, such as 28 %. While recent improvements in the culture specimen selection and specialized specimen handling have enhanced sensitivity, the overall detection efficiency remains unsatisfactory [7]. Secondly, the extended duration required to obtain culture results impedes the timely treatment of PJI. Lastly, many patients with suspected PJI receive antibiotic treatment at local hospitals prior to consultation, significantly reducing the detection rate of pathogenic microbial culture.

In recent years, there has been rapid development in gene sequencing technology, which has found application in the diagnosis of pathogenic microorganisms. The first-generation gene sequencing focused on obtaining the sequence of the human genetic map [8], but due to its low throughput and high cost, large-scale sequencing was impractical. Second-generation gene sequencing addressed the low throughput issue of first-generation sequencing, reducing the sequencing time. Nevertheless, it had limitations such as short read lengths and the need for gene amplification, leading to information loss for genes with low abundance [9]. On the other hand, third-generation sequencing (TGS) uses nanopore technology to detect changes in electrical signals caused by the passage of DNA bases through the nanopores [10]. TGS offers advantages such as high throughput, long read lengths, and no requirement for gene amplification [10]. Each base of the DNA molecule passing through the nanopore produces a distinct change in the electrical signal, enabling base identification and gene sequencing [11]. TGS technology offers several advantages over traditional sequencing methods. Firstly, it eliminates the need for gene amplification, thereby minimizing errors that can occur during amplification and improving accuracy. Secondly, TGS provides longer read lengths, reaching 2 Mb, allowing for the use of long-read sequencing data for precise gene reconstruction and resulting in an accurate genetic map of pathogenic bacteria. Moreover, the extended read length of TGS enables the detection of repetitive sequences and structural variants within the genome. Thirdly, TGS allows for dynamic, real-time sequencing, enabling rapid acquisition of results within a few hours. TGS shows promise for detecting pathogenic microorganisms [12,13], but its application in the detection of pathogenic bacteria in PJI has not been reported.

Therefore, this study aimed to conduct a comprehensive comparison between TGS and conventional culture for the detection of the causative microorganism of PJI. This investigation aimed to gather strong evidence that supports the application of TGS and encourages its integration into clinical practice.